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Llm Developer Jobs in Rochester, NY (NOW HIRING)

... LLM optimization - Implementing data integration solutions using AWS, Azure, GCP - Utilizing AWS CloudFormation, Azure Resource Manager, Terraform - Building and deploying DevOps pipelines with cloud ...

AI Engineer

Rochester, NY · On-site +1

$124K - $160K/yr

Deploy AI models into production environments, collaborate with DevOps and IT teams to ensure ... LLM tuning and tools like LangChain. * Applicants must be authorized to work for any employer in ...

AI Engineer

Rochester, NY · On-site

$124K - $160K/yr

Deploy AI models into production environments, collaborate with DevOps and IT teams to ensure ... LLM tuning and tools like LangChain. * Applicants must be authorized to work for any employer in ...

AI Automation Engineer -Remote

Geneseo, NY · On-site +1

$202.38K - $234.20K/yr

Experience creating LLM-backed tools involving prompt engineering and automated evals * 5+ years of experience in full-stack development with strong skills in Python, React and JavaScript * Excellent ...

AI Automation Engineer -Remote

Rochester, NY · On-site +1

$202.38K - $234.20K/yr

Experience creating LLM-backed tools involving prompt engineering and automated evals * 5+ years of experience in full-stack development with strong skills in Python, React and JavaScript * Excellent ...

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Llm Developer information

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$25

$49

$78

How much do llm developer jobs pay per hour?

As of May 31, 2026, the average hourly pay for llm developer in Rochester, NY is $49.50, according to ZipRecruiter salary data. Most workers in this role earn between $38.89 and $60.00 per hour, depending on experience, location, and employer.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive in the Llm Developer position, and why are they important?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What are the typical daily tasks and responsibilities of an LLM Developer?

As an LLM Developer, your daily responsibilities often include designing, fine-tuning, and evaluating large language models to meet specific application needs. You may work on tasks such as data preprocessing, model training, performance benchmarking, and error analysis, frequently collaborating with data scientists, research engineers, and product managers. Keeping up to date with the latest advancements in NLP and integrating new techniques into production models is also a key part of the role. These tasks are usually performed in a team-oriented environment where clear communication and iterative experimentation are highly valued.

What is the salary of LLM engineer?

The salary of an LLM (Large Language Model) engineer typically ranges from $100,000 to $180,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in deep learning and NLP can earn higher compensation, often exceeding $200,000 with bonuses and stock options.
What are popular job titles related to Llm Developer jobs in Rochester, NY? For Llm Developer jobs in Rochester, NY, the most frequently searched job titles are:
What job categories do people searching Llm Developer jobs in Rochester, NY look for? The top searched job categories for Llm Developer jobs in Rochester, NY are:
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Cyber AI Governance and Privacy Senior Consultant

Cyber AI Governance and Privacy Senior Consultant

Deloitte

Rochester, NY • On-site

Other

Posted 18 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 6/5/2026.

Work You'll Do

You will lead and deliver AI governance, privacy, and security outcomes across the AI lifecycle, including:

  • Designing pragmatic AI governance operating models (intake, risk tiering, approvals, documentation standards, exception handling, and audit readiness) with a focus on GenAI and agentic AI deployments.
  • Building and maintaining AI system inventories (models, agents, tools, data sources, integrations), with clear ownership, intended use, risk classification, and change-control expectations.
  • Conducting AI risk assessments for privacy, security, model risk, and misuse-including prompt injection, sensitive data exposure, excessive agency, and overreliance-and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions: human-in-the-loop patterns, tool access controls, safe retrieval and grounding practices, logging/monitoring, token and data minimization, and incident response playbooks.
  • Implementing "governance in the workflow" by integrating governance checkpoints into product and engineering delivery (architecture reviews, release gates, evaluation requirements, documentation automation, and evidence capture).
  • Standing up or enhancing evaluation and monitoring approaches for GenAI systems: test plans, safety and quality metrics, red teaming workflows, and reporting dashboards for leaders and risk stakeholders.
  • Partnering cross-functionally with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science to drive adoption and ensure governance guidance is usable, measurable, and repeatable.

The Team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in one or more of the following: AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Demonstrated experience translating policies and regulatory expectations into operational workflows, artifacts, and controls (e.g., intake processes, inventories, decision logs, risk registers, RACI, playbooks).
  • Working knowledge of AI/ML/LLM systems and delivery lifecycles sufficient to assess real deployment risks and mitigations (training vs. RAG vs. fine-tuning vs. tool use, data dependencies, integration patterns).
  • Software development fluency: ability to collaborate with engineering teams on implementation details; ability to prototype or automate governance workflows in Python/SQL and to understand CI/CD and cloud deployment basics.
  • Practical experience with privacy program execution and artifacts (PIAs/DPIAs, vendor reviews, data inventories, data minimization, retention, and access control principles).
  • Ability to communicate clearly with both technical and non-technical stakeholders and produce executive-ready reporting.
  • Ability to travel 0-50%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available.

Preferred

  • Previous consulting or Big 4 experience.
  • Hands-on experience operationalizing AI governance aligned to frameworks such as the NIST AI RMF and/or ISO/IEC 42001, with awareness of risk-based AI regulatory regimes (e.g., EU AI Act).
  • Experience with GenAI safety and evaluation practices (prompt injection testing, jailbreak resilience, hallucination measurement, toxicity/harm scoring, grounding effectiveness).
  • Familiarity with governance tooling and workflow platforms (e.g., OneTrust, GRC platforms, ticketing/workflow systems) and how to integrate them into engineering delivery.
  • Certifications such as CIPP/US, CIPM, IAPP AIGP, CISM, or CISSP.
  • Prior experience in cyber or enterprise security contexts (data security, identity, audit logging, secure SDLC).
  • Experience designing Human-in-the-Loop escalation pathways, exception handling, and automated safety protocols for highly autonomous systems.

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 $118,700 - 218,600. 

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.

#CyberDTP27

Qualifications:

We are seeking an AI Governance and Privacy Specialist who can operationalize responsible AI in real systems-especially agentic AI and LLM-enabled applications. This role blends governance and privacy expertise with enough software development fluency to create developer-ready guidance, implement controls-as-code patterns, and stand up measurable evaluation and monitoring workflows.

As a Senior Consultant, you will help clients and internal delivery teams move from AI principles to practices: risk tiering, model and agent inventories, technical guardrails, governance workflows integrated into the SDLC, and evidence artifacts suitable for audits and regulators.

Recruiting for this role ends on 6/5/2026.

Work You'll Do

You will lead and deliver AI governance, privacy, and security outcomes across the AI lifecycle, including:

  • Designing pragmatic AI governance operating models (intake, risk tiering, approvals, documentation standards, exception handling, and audit readiness) with a focus on GenAI and agentic AI deployments.
  • Building and maintaining AI system inventories (models, agents, tools, data sources, integrations), with clear ownership, intended use, risk classification, and change-control expectations.
  • Conducting AI risk assessments for privacy, security, model risk, and misuse-including prompt injection, sensitive data exposure, excessive agency, and overreliance-and translating findings into implementable mitigations.
  • Establishing technical control guidance for teams building agentic AI solutions: human-in-the-loop patterns, tool access controls, safe retrieval and grounding practices, logging/monitoring, token and data minimization, and incident response playbooks.
  • Implementing "governance in the workflow" by integrating governance checkpoints into product and engineering delivery (architecture reviews, release gates, evaluation requirements, documentation automation, and evidence capture).
  • Standing up or enhancing evaluation and monitoring approaches for GenAI systems: test plans, safety and quality metrics, red teaming workflows, and reporting dashboards for leaders and risk stakeholders.
  • Partnering cross-functionally with Cybersecurity, Privacy, Legal, Risk, Engineering, and Data Science to drive adoption and ensure governance guidance is usable, measurable, and repeatable.

The Team

You will join a cross-functional group working at the intersection of cyber, privacy, governance, and emerging AI delivery. The team helps organizations scale AI responsibly by combining governance and engineering patterns so teams can innovate faster without compromising trust.

Qualifications

Required

  • Bachelor's degree or equivalent practical experience.
  • 4+ years of experience in one or more of the following: AI governance, data privacy, security risk management, compliance and controls, AI product risk, model risk management, or technology risk consulting.
  • Demonstrated experience translating policies and regulatory expectations into operational workflows, artifacts, and controls (e.g., intake processes, inventories, decision logs, risk registers, RACI, playbooks).
  • Working knowledge of AI/ML/LLM systems and delivery lifecycles sufficient to assess real deployment risks and mitigations (training vs. RAG vs. fine-tuning vs. tool use, data dependencies, integration patterns).
  • Software development fluency: ability to collaborate with engineering teams on implementation details; ability to prototype or automate governance workflows in Python/SQL and to understand CI/CD and cloud deployment basics.
  • Practical experience with privacy program execution and artifacts (PIAs/DPIAs, vendor reviews, data inventories, data minimization, retention, and access control principles).
  • Ability to communicate clearly with both technical and non-technical stakeholders and produce executive-ready reporting.
  • Ability to travel 0-50%, on average, based on client and project needs.
  • Limited immigration sponsorship may be available.

Preferred

  • Previous consulting or Big 4 experience.
  • Hands-on experience operationalizing AI governance aligned to frameworks such as the NIST AI RMF and/or ISO/IEC 42001, with awareness of risk-based AI regulatory regimes (e.g., EU AI Act).
  • Experience with GenAI safety and evaluation practices (prompt injection testing, jailbreak resilience, hallucination measurement, toxicity/harm scoring, grounding effectiveness).
  • Familiarity with governance tooling and workflow platforms (e.g., OneTrust, GRC platforms, ticketing/workflow systems) and how to integrate them into engineering delivery.
  • Certifications such as CIPP/US, CIPM, IAPP AIGP, CISM, or CISSP.
  • Prior experience in cyber or enterprise security contexts (data security, identity, audit logging, secure SDLC).
  • Experience designing Human-in-the-Loop escalation pathways, exception handling, and automated safety protocols for highly autonomous systems.

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 $118,700 - 218,600. 

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.

#CyberDTP27

Education:Bachelor's DegreeEmployment Type:

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