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Evidence Collection Jobs in Indiana (NOW HIRING)

Office LPN-POHC

Fort Wayne, IN

$23.75 - $32.25/hr

Responsible for evidence collection, documentation, and analysis according to federal regulations for forensic testing. Collects blood, urine, and/or hair samples. Provides immunizations, medications ...

Office LPN-POHC

Fort Wayne, IN · On-site

$13.70 - $23.29/hr

Responsible for evidence collection, documentation, and analysis according to federal regulations for forensic testing. Collects blood, urine, and/or hair samples. Provides immunizations, medications ...

Office LPN-POHC

Fort Wayne, IN

$23.75 - $32.25/hr

Responsible for evidence collection, documentation, and analysis according to federal regulations for forensic testing. Collects blood, urine, and/or hair samples. Provides immunizations, medications ...

Medical Assistant-POHC

Fort Wayne, IN

$16.25 - $21/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Fort Wayne, IN · On-site

$16.25 - $21/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Logansport, IN

$16.50 - $21/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Fort Wayne, IN · On-site

$16.25 - $21/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Fort Wayne, IN · On-site

$11.51 - $17.27/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Fort Wayne, IN · On-site

$11.51 - $17.27/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Fort Wayne, IN · On-site

$16.25 - $21/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

Medical Assistant-POHC

Fort Wayne, IN · On-site

$16.25 - $21/hr

Evidence collection, documentation, and analysis according to federal regulations for forensic testing. Completes physician orders. Discharges patients assuring accurate completion of physician ...

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Showing results 1-20

Evidence Collection information

See Indiana salary details

$9

$19

$28

How much do evidence collection jobs pay per hour?

As of Jul 29, 2026, the average hourly pay for evidence collection in Indiana is $19.06, according to ZipRecruiter salary data. Most workers in this role earn between $15.34 and $21.97 per hour, depending on experience, location, and employer.

How to become an evidence collector?

To become an evidence collector, individuals typically need a high school diploma or equivalent, and some roles may require post-secondary education or specialized training in forensic science or law enforcement. Skills in attention to detail, documentation, and knowledge of evidence handling procedures are essential, and certifications in crime scene investigation can enhance job prospects.

What are the key skills and qualifications needed to thrive in Evidence Collection, and why are they important?

To thrive in Evidence Collection, you need a solid understanding of forensic science principles, attention to detail, and training in crime scene protocols, often demonstrated through relevant certifications or law enforcement experience. Familiarity with evidence management systems, digital documentation tools, and chain-of-custody procedures is crucial. Strong observation, communication, and critical thinking skills help professionals accurately document and handle sensitive materials. These skills are vital for ensuring the integrity and admissibility of evidence in legal proceedings.

What is the difference between Evidence Collection vs Evidence Technician?

AspectEvidence CollectionEvidence Technician
CertificationsMay require law enforcement or forensic certificationsOften requires forensic or law enforcement certifications
Work EnvironmentFieldwork at crime scenes, labs, or courtroomsCrime scene labs, field sites, or forensic facilities
Employer & IndustryLaw enforcement agencies, forensic labsForensic laboratories, law enforcement agencies
Search & Comparison IntentUnderstanding roles in evidence gatheringClarifying forensic lab or crime scene technician roles

Evidence Collection involves gathering physical evidence at crime scenes or labs, often requiring law enforcement or forensic certifications. Evidence Technicians typically work within forensic labs or crime scene units, focusing on processing and analyzing evidence. While both roles support criminal investigations, Evidence Collection emphasizes fieldwork, whereas Evidence Technicians focus on lab analysis and documentation.

Can I become a CSI without being a cop?

Crime Scene Investigators (CSIs) are typically not required to be police officers, but they often have backgrounds in forensic science, criminal justice, or related fields. Many CSIs are civilians who work alongside law enforcement, using skills in evidence collection, fingerprint analysis, and crime scene documentation. Certification and specialized training in forensic techniques are usually necessary for this role.

What are some common challenges faced by evidence collection professionals in the field?

Evidence collection professionals often encounter challenges such as working in unpredictable environments, maintaining chain of custody for all items, and ensuring that evidence is not contaminated or compromised. They must also stay current with evolving technology and legal standards to properly document and handle evidence. Effective communication and collaboration with law enforcement, forensic specialists, and legal teams are essential to ensure the integrity and admissibility of collected evidence in court.

How hard is it to get into the CSI?

Getting into a Crime Scene Investigator (CSI) role typically requires a background in criminal justice, forensic science, or a related field, along with relevant experience or training. Many positions also prefer candidates with certifications such as the Certified Crime Scene Analyst (CCSA) and strong attention to detail, analytical skills, and the ability to work in high-pressure environments. Competition can be high, and some agencies require passing background checks and physical fitness tests.

What is evidence collection?

Evidence collection refers to the process of identifying, gathering, preserving, and documenting physical or digital evidence from a crime scene or investigation site. This crucial step ensures that evidence is handled properly to maintain its integrity for analysis and use in legal proceedings. Proper evidence collection is essential for building a solid case and upholding the chain of custody, which protects the evidence from tampering or contamination.

Does CSI make good money?

Evidence collection specialists, or crime scene investigators (CSIs), typically earn a median annual salary that varies by location and experience, often ranging from $40,000 to $70,000. Salaries can increase with specialized training, certifications, and years of experience, and the job may require shift work and attention to detail.
What are popular job titles related to Evidence Collection jobs in Indiana? For Evidence Collection jobs in Indiana, the most frequently searched job titles are:
Infographic showing various Evidence Collection job openings in Indiana as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 17% Part Time, 1% Temporary, and 3% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $39,654 per year, or $19.1 per hour.

Cyber Manager - Technology Resilience

Deloitte

Indianapolis, IN

Other

Posted 2 days ago

New


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 91 frontline employees who took The Breakroom Quiz

56th of 150 rated financial services


Job description

Technical Resilience FDE Manager

As a Manager, AI Engineering (Forward Deployed Engineer) in Deloitte Cyber, you will be embedded in a client's environment to design, build, and ship production-grade AI capabilities using the client's own data, systems, and workflows. This role is administratively aligned to the Cyber Resilience practice, and the applied use cases you build will typically span disaster recovery orchestration, control and evidence collection, continuity and recovery planning, and third-party resilience monitoring - but these are application areas your AI engineering work supports, not prerequisites requiring deep resilience or audit domain credentials. You will combine strong engineering depth with the judgment to translate ambiguous client problems into working AI systems, shape technical solutions during pursuits, and build reusable accelerators that raise the bar across engagements. 

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Manager on a client-embedded AI engineering team, you will be responsible for:

          Designing and hands-on building AI-enabled solutions (agents, retrieval/RAG pipelines, automation workflows) directly inside a client's environment, using their live data and systems

          Ensuring deployed AI systems meet production bars for evaluation, guardrails, observability, reliability, security, and cost/performance management

          Building automated controls and response workflows that support disaster recovery orchestration and continuity and recovery operations

          Building AI-enabled control and evidence collection capabilities - automating inventory, monitoring, and evidence gathering to produce audit-ready evidence across cybersecurity, continuity, and third-party resilience programs

          Translating client business needs - including resilience use cases such as continuity planning and recovery orchestration - into working, production-grade AI technical solutions aligned to target architecture

          Leading the hands-on design, integration, deployment, and operation of production-grade solutions, including troubleshooting and resolving technical issues within scope

          Shaping technical solutions during pursuits by leading demonstrations, proofs of concept, prototypes, effort estimation, and pricing inputs

          Leading client-facing workshops, demonstrations, and training sessions to drive adoption of new AI capabilities, and supporting operational handoff so client teams can run and maintain what you build

          Managing client delivery by overseeing scope, timelines, quality, customer satisfaction, and continuous improvement across engagements

          Contributing to and extending existing reusable accelerators, documentation, and engineering best practices to build team and client capability

          Mentoring engineers and leading individual workstreams within the engagement

A successful candidate would possess these skills:

          Ability to work independently and collaborate as part of a team

          Effective written and verbal communication skills, meticulous attention to detail and quality of work product, ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment

          Ability to build and sustain professional relationships, lead projects or workstreams and meet deadlines

          Ability to mentor and provide clear guidance to others

The team

Deloitte's Cyber Resilience practice helps organizations anticipate, withstand, and recover from disruption - spanning disaster recovery orchestration, business continuity and recovery planning, and third-party resilience, as well as the underlying architecture, inventory, monitoring, and control and evidence collection programs that demonstrate cybersecurity and continuity posture to regulators and stakeholders. The team is building AI-driven capabilities - including automated controls, continuous monitoring, response workflows, and audit-ready evidence generation - designed to help clients strengthen resilience posture, simplify complexity, and respond with greater speed and confidence when disruption occurs.

The FDE is embedded directly in a client's environment to build and ship AI capabilities using the client's own data, systems, and workflows, with resilience and recovery use cases (e.g., disaster recovery orchestration, control and evidence collection, response workflows, third-party resilience monitoring) as the applied domain for that AI engineering work.

Qualifications

Required:

          Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; alternatively, equivalent demonstrated experience

          8-10+ years of hands-on software engineering experience building and deploying production-grade systems using one or more of the following - Python, Java, or Node.js

          5+ years of experience translating client or business requirements into target-state solution architectures using REST APIs, microservices, event-driven architectures, or serverless components

          2+ years of experience delivering solutions on Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including containers, continuous integration and continuous delivery pipelines, and version control tools

          2+ years of hands-on experience designing, building, and deploying generative AI or large language model solutions (e.g., agents, RAG, tool-calling) in a client or production environment - beyond proof-of-concept

          Hands-on experience applying production AI engineering practices - evaluation, guardrails, observability, reliability, security, and cost/performance management - to deployed models and agentic systems

          Ability to work directly and independently within a client's environment and codebase, including navigating unfamiliar systems and undocumented workflows

          Ability to build automation that integrates with monitoring, ITSM, or GRC platforms to support control monitoring, evidence collection, and response workflows

          Experience leading client enablement activities - workshops, demonstrations, adoption planning, and operational handoff - to help client teams adopt and sustain delivered solutions

          Experience contributing to and extending reusable AI accelerators, tools, or frameworks that speed up delivery across engagements

          Exposure to disaster recovery, business continuity, or third-party resilience concepts is a plus but not required - domain onboarding will be provided

          Ability to travel 25-50%, on average, based on the work you do and the clients and industries/sectors you serve

          Limited immigration sponsorship may be available

Preferred:

          Front-end / full-stack breadth - JavaScript/TypeScript and a modern UI framework (React / Next.js) for building demo apps and lightweight delivery tooling leveraging agentic coding tools (e.g., Claude Code, Codex, Cursor, etc.)

          Experience with agent orchestration or LLM application frameworks (e.g., LangChain, LlamaIndex, Model Context Protocol, Bedrock Agents, Azure AI Foundry, Vertex AI)

          Experience with GRC, ITSM, or monitoring/observability platforms (e.g., ServiceNow, Archer, Splunk, Datadog) relevant to control monitoring and evidence automation

          Familiarity with control frameworks or standards (NIST CSF, ISO 22301, SOC 2) sufficient to model them in code - audit or assessor experience not required

          Experience designing AI-enabled use cases within resilience or continuity workflows (e.g., disaster recovery orchestration, control and evidence automation, third-party resilience monitoring) is a plus, though not a prerequisite

          Prior experience in a forward-deployed, embedded, or client-site engineering model (vs. offshore/remote delivery only)

          Industry depth in a regulated vertical (financial services, healthcare, public sector) and exposure to associated compliance regimes (SOX, PCI DSS, FFIEC, HIPAA, GDPR)

          Kubernetes, GitOps, and advanced cloud-native delivery patterns

          Familiarity with ML frameworks (PyTorch, TensorFlow) and model evaluation

          Relevant certifications - cloud (AWS/Azure/GCP) or AI/ML-specific certifications

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 - 306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.


#CyberCDR27

Qualifications:

Technical Resilience FDE Manager

As a Manager, AI Engineering (Forward Deployed Engineer) in Deloitte Cyber, you will be embedded in a client's environment to design, build, and ship production-grade AI capabilities using the client's own data, systems, and workflows. This role is administratively aligned to the Cyber Resilience practice, and the applied use cases you build will typically span disaster recovery orchestration, control and evidence collection, continuity and recovery planning, and third-party resilience monitoring - but these are application areas your AI engineering work supports, not prerequisites requiring deep resilience or audit domain credentials. You will combine strong engineering depth with the judgment to translate ambiguous client problems into working AI systems, shape technical solutions during pursuits, and build reusable accelerators that raise the bar across engagements. 

Recruiting for this role ends on 12/31/2026.

Work you'll do

As a Manager on a client-embedded AI engineering team, you will be responsible for:

          Designing and hands-on building AI-enabled solutions (agents, retrieval/RAG pipelines, automation workflows) directly inside a client's environment, using their live data and systems

          Ensuring deployed AI systems meet production bars for evaluation, guardrails, observability, reliability, security, and cost/performance management

          Building automated controls and response workflows that support disaster recovery orchestration and continuity and recovery operations

          Building AI-enabled control and evidence collection capabilities - automating inventory, monitoring, and evidence gathering to produce audit-ready evidence across cybersecurity, continuity, and third-party resilience programs

          Translating client business needs - including resilience use cases such as continuity planning and recovery orchestration - into working, production-grade AI technical solutions aligned to target architecture

          Leading the hands-on design, integration, deployment, and operation of production-grade solutions, including troubleshooting and resolving technical issues within scope

          Shaping technical solutions during pursuits by leading demonstrations, proofs of concept, prototypes, effort estimation, and pricing inputs

          Leading client-facing workshops, demonstrations, and training sessions to drive adoption of new AI capabilities, and supporting operational handoff so client teams can run and maintain what you build

          Managing client delivery by overseeing scope, timelines, quality, customer satisfaction, and continuous improvement across engagements

          Contributing to and extending existing reusable accelerators, documentation, and engineering best practices to build team and client capability

          Mentoring engineers and leading individual workstreams within the engagement

A successful candidate would possess these skills:

          Ability to work independently and collaborate as part of a team

          Effective written and verbal communication skills, meticulous attention to detail and quality of work product, ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment

          Ability to build and sustain professional relationships, lead projects or workstreams and meet deadlines

          Ability to mentor and provide clear guidance to others

The team

Deloitte's Cyber Resilience practice helps organizations anticipate, withstand, and recover from disruption - spanning disaster recovery orchestration, business continuity and recovery planning, and third-party resilience, as well as the underlying architecture, inventory, monitoring, and control and evidence collection programs that demonstrate cybersecurity and continuity posture to regulators and stakeholders. The team is building AI-driven capabilities - including automated controls, continuous monitoring, response workflows, and audit-ready evidence generation - designed to help clients strengthen resilience posture, simplify complexity, and respond with greater speed and confidence when disruption occurs.

The FDE is embedded directly in a client's environment to build and ship AI capabilities using the client's own data, systems, and workflows, with resilience and recovery use cases (e.g., disaster recovery orchestration, control and evidence collection, response workflows, third-party resilience monitoring) as the applied domain for that AI engineering work.

Qualifications

Required:

          Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field; alternatively, equivalent demonstrated experience

          8-10+ years of hands-on software engineering experience building and deploying production-grade systems using one or more of the following - Python, Java, or Node.js

          5+ years of experience translating client or business requirements into...


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