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Ai Reliability Engineer Jobs in Indiana (NOW HIRING)

Kobie Marketing

AI Engineer

Indianapolis, IN · Remote

We're looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production.

Telnyx

Software Engineer, GTM AI - Python

Brazil, IN

... reliability * Design tool-use patterns for AI agents - structured function calling, multi-step ... Background in growth engineering, marketing automation, or revenue operations tooling * Experience ...

Deloitte

Google AI Lead Architect

Indianapolis, IN · On-site

$52.75 - $72.50/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and ... reliability, security, and cost. * Design, fine-tune, evaluate, and govern LLM solutions with ...

Relativity

Software Engineer

Indianapolis, IN · On-site

WHAT WE DO At Relativity, engineers don't just write code. They build the systems that power AI ... AI traffic across regions and providers, protect downstream services from reliability risks, and ...

Salesforce, Inc.

AI Solution Orchestrator

Indianapolis, IN

$52.75 - $68/hr

... reliability * Prompt Best Practices: Apply established prompt engineering techniques (chain-of ... AI Tooling Proficiency: Proficiency in the latest AI Tooling and best practices * Excellent ...

Salesforce, Inc.

AI Solution Orchestrator

Indianapolis, IN · On-site

$52.75 - $68/hr

... reliability * Prompt Best Practices: Apply established prompt engineering techniques (chain-of ... AI Tooling Proficiency: Proficiency in the latest AI Tooling and best practices * Excellent ...

Pwc

US Tech - AI Engineering Manager

Indianapolis, IN

$73K - $244K/yr

... AI solutions. Responsibilities - Mentor junior engineers and foster their growth - Maintain ... reliability and security - Working with product owners, UX, data science, and security teams to ...

Allied Solutions LLC

Senior AI Architect

Carmel, IN · On-site

Design solutions for scalability, reliability, observability, privacy, compliance, supportability ... Mentor engineers, analysts, and business partners through hands-on collaboration, technical ...

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Ai Reliability Engineer information

What are the key skills and qualifications needed to thrive as an AI Reliability Engineer, and why are they important?

To thrive as an AI Reliability Engineer, you need a solid background in computer science or engineering, expertise in AI/ML concepts, and experience with software testing and reliability methodologies. Familiarity with tools like TensorFlow, PyTorch, CI/CD pipelines, and reliability testing frameworks, along with certifications in cloud platforms (e.g., AWS Certified Machine Learning), is highly valuable. Analytical thinking, problem-solving abilities, and strong collaboration skills set top performers apart in this role. These skills ensure robust, dependable AI systems that meet performance standards and maintain trust in critical applications.

What is the difference between Ai Reliability Engineer vs Data Scientist?

AspectAi Reliability EngineerData Scientist
Required CredentialsBachelor's or master's in CS, engineering, or related; certifications in AI/MLBachelor's or master's in CS, statistics, or related; certifications in data analysis or ML
Work EnvironmentTech companies, AI-focused teams, engineering departmentsResearch labs, tech firms, analytics teams
Employer & Industry UsageAI product development, machine learning systems, reliability testingData analysis, predictive modeling, business insights

While both roles involve AI and ML, Ai Reliability Engineers focus on ensuring AI system robustness and uptime, whereas Data Scientists analyze data to generate insights and models. The roles often collaborate but serve different primary functions within AI projects.

What are AI Reliability Engineers?

AI Reliability Engineers are professionals responsible for ensuring that artificial intelligence systems function reliably, safely, and effectively over time. They work on monitoring AI models in production, identifying and mitigating potential failures, and improving the robustness of AI systems. Their tasks often include testing, validation, performance monitoring, and implementing best practices for maintaining AI infrastructure. By focusing on reliability, they help organizations deploy AI solutions that are dependable and trustworthy in real-world environments.

What are some common challenges Ai Reliability Engineers face when ensuring model robustness in production environments?

Ai Reliability Engineers often encounter challenges such as monitoring AI model performance for drift or unexpected behavior, managing data quality issues, and implementing automated alerting systems for anomalies. In production, it's crucial to ensure that AI models operate consistently and remain reliable under varying conditions and data inputs. Collaborating closely with data scientists, software engineers, and DevOps teams is essential to address these challenges and to continuously improve model reliability and uptime.
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Ai Reliability Engineer jobs near you
AI Engineer

AI Engineer

Kobie Marketing

Indianapolis, IN • Remote

Full-time

Re-posted 3 days ago

Job description

Join a National Top Workplace 
 
Named a Top Workplace in the USA and Top Remote Workplace, Kobie is where the best minds in loyalty come together, driven by passion and innovation. We're always looking for talented individuals who are ready to join a collaborative, growth-focused culture. As a partner to some of the world's most recognized brands, we are leaders in loyalty, helping brands build lasting emotional connections with their consumers. 
 
Join Us from Anywhere 
While our headquarters are nestled in sunny St. Petersburg, Florida, Kobie embraces a flexible work environment, offering teammates the freedom to work remotely. We understand the importance of work-life balance and support our team with: 

         Flexible Time Off to recharge when needed 
         Nine Company-Wide Holidays 
         A diverse suite of benefits prioritizing your growth, development, and personal well-being 

Discover more about our perks and benefits here. 
 
Kobie is a values-led organization where we believe that everyone is a leader, regardless of their position or role. 


About the team and what we'll build together

Kobie runs some of the largest loyalty programs in the world. We're building an internal agent platform on Amazon AgentCore that automates analyst workflows, surfaces insights from program data in Snowflake, and gives our teams and clients an LLM-native way to work with complex loyalty logic.

We're looking for a hands-on AI Engineer to ship on that platform: building agent harnesses, writing the tools those agents call, and owning the reliability and evaluation of what goes to production. This is not a research role. You'll prototype, ship, monitor, and iterate on features used by real teams

Our team tends to be people who reason carefully, ship working code,and pick up new tools without a lot of handholding. There's no single path into this role. We value the impact of what you've built and your track record of building things that hold up.

How you will make an impact

Agent Development

  • Build agent harnesses in Python using LangChain and LangGraph, including tool-calling, structured outputs (Pydantic/JSON schema), retries, streaming, and memory
  • Package agent harnesses for the AgentCore Runtime with appropriate context, tools, skills, and subagents that fit cleanly into production flows and scenarios
  • Write the tools and skills agents use  API integrations, SQL queries against Snowflake, Snowflake backed knowledge retrieval with clear contracts and Pydantic validation

Evaluation and Reliability

  • Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore Evaluations, and wire them into CI
  • Implement guardrails around tool execution: auth scoping, input/output validation, PII and prompt-injection protections, and hallucination mitigation
  • You own what you ship: prototype, deploy through Amazon AgentCore, monitor traces, and fix it when it breaks

Collaboration

  • Partner with data engineers on Snowflake backed retrieval patterns (Cortex Analyst and Cortex Search Services)
  • Contribute to refining our internal engineering patterns as the stack evolves

What you need to be successful

Required

  • 3+ years of professional Python, with production experience building and operating services
  • 1+ years of hands-on work with LLMs in production: prompt/context engineering, tool/function calling, structured outputs, RAG
  • Working knowledge of LangChain/LangGraph or a comparable framework like AgentCore Strands, CrewAI, or Semantic Kernel
  • Experience with LLM observability tools: Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry
  • Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression)
  • Fluency with Git, Docker, and modern API frameworks
  • Clear written communication and the judgment to know when something is ready to ship

A bachelor's degree is not required. Equivalent practical experience: including bootcamps, self-taught work, career changes, or non-CS technical degrees counts.

Strongly Preferred

  • Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory, policy, guardrails, observability, awscli, evaluations
  • Experience with Snowflake, Snowpark, or Snowflake Cortex
  • Fluency in writing and reading SQL, as well as understanding semantic models.
  • Familiarity with multi-agent patterns: supervisor/router, subagent/handoff, reflection, human-in-the-loop
  • A considered view on where agents should and shouldn't act and comfort pushing back when "let's add an agent" isn't the right answer
  • Experience in Loyalty, MarTech, AdTech, or a comparable data rich B2B domain
Who we are  As a trusted partner, Kobie delivers market-leading, end-to-end loyalty solutions designed to enable customer experiences for the world's most successful brands. We do this with a strategy-led technology approach that uncovers the truth behind what drives consumers on an emotional level. We believe that our team's passion and expertise are the driving forces behind our success and are proud to be named a Top Workplaces in the USA, where the best and brightest in loyalty drive our mission of growing enterprise value through loyalty. 
 
A place for all We celebrate and embrace diversity at Kobie! 
Employment at Kobie is based solely on an individual's merit and qualifications, which are directly related to professional competence. We do not discriminate against any teammate or applicant because of race,color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy, or any other characteristic protected by applicable law. 
 
We are fiercely committed to fostering a workplace where teammates can bring their authentic selves to work every day. Our DEI initiatives, including various committees, ensure that principles of equity, diversity, and inclusion are deeply ingrained throughout Kobie. While our leadership team fully supports our policy of nondiscrimination and equal opportunity, it is the responsibility of all teammates to uphold these values. 
 
Ready to join us? If you're ready to make an impact and grow in a supportive, innovative environment, we'd love to hear from you. Apply today and join the best and brightest in loyalty! 
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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