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Senior AI Machine Learning Engineer (Agentic Systems & LLM Evaluation)
- Pay
- Pay not listed
- Work setting
Remote — work setting source
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingBuild agentic systems for different software development lifecycle (SDLC) personas
Design and implement LLM evaluation test cases using LLM judges and deterministic methods
Evaluate model performance and reliability with LangSmith, LangFuse, or MLFlow
Develop and fine-tune prompt frameworks to align LLMs with agent requirements
Monitor, debug, and optimize AI system performance through testing and automation
From the employer’s posting
Build agentic systems tailored to various Software Development Lifecycle (SDLC) personas
Design and implement robust evaluation test cases for LLMs using LLMs as judges and deterministic methodologies
Evaluate model performance and ensure reliability using tools such as LangSmith, LangFuse, or MLFlow
Develop and fine-tune prompt frameworks to align LLMs with diverse agent requirements
Monitor, debug, and optimize AI systems’ performance using advanced testing and automation practices
Posting record
Report an errorActively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 1, 20262 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 4, 2026
- Employer says posted
- Sep 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
656 open jobs
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Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- MLflow
Where the posting names them
We are seeking a highly skilled Senior AI Machine Learning Engineer to lead the development of intelligent agentic systems and drive the evaluation of large language models (LLMs). In this role, you will collaborate with stakeholders to design and implement powerful agents, design robust evaluation frameworks, and contribute to advancing the effectiveness and reliability of AI systems. Responsibilities Build agentic systems tailored to various Software Development Lifecycle (SDLC) personas, translating requirements into actionable implementations Partner closely with cross-functional teams to understand workflows and ensure alignment with stakeholder needs Design and implement robust evaluation test cases for LLMs using LLMs as judges and deterministic methodologies Evaluate model performance and ensure reliability using tools such as LangSmith, LangFuse, or MLFlow Develop and fine-tune prompt frameworks to align LLMs with diverse agent requirements Utilize programming expertise in Python and AI/ML frameworks to enhance agentic systems' capabilities Monitor, debug, and optimize AI systems’ performance using advanced testing and automation practices Leverage modern SDKs like LangGraph or similar frameworks to efficiently build intelligent workflows Foster continuous improvement by incorporating feedback, testing outcomes, and insights into future iterations Act as a thought leader on AI testing standards, governance, and best practices in agentic system development Requirements 3+ years of experience in AI engineering, with emphasis on LLMs and agentic systems Knowledge of modern testing standards and practices applied to agentic systems Strong programming and development skills in Python, with usage of AI/ML frameworks and libraries Familiarity with evaluation and monitoring tools such as LangSmith, LangFuse, or MLFlow Competency in using SDKs like LangGraph or similar frameworks for agentic system development Understanding of LLM concepts, including prompt engineering and fine-tuning methodologies Knowledge of testing frameworks and automation tools for validating AI systems Analytical and problem-solving skills, with a focus on delivering reliable and effective solutions Proficiency in communication and collaboration, ensuring successful teamwork across roles Capability to work independently, delivering high-quality AI solutions in a dynamic environment Excellent written and spoken English (B2+ level) Nice to have Experience writing agentic systems using SDKs like LangGraph or similar technologies Familiarity with evaluation tools such as LangSmith, LangFuse, or MLFlow Understanding of AI governance, safety, and ethical considerations in agentic systems Showcase of enterprise-grade AI solutions with multiple integrations and workflows
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
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About the role
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
US government figures for computer and information research scientists
- Median yearly pay, May 2025
- $140,300
- Expected change, 2025 to 2035
- 21.8% more jobsagainst 3.5% for all jobs
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
Job description
We are seeking a highly skilled Senior AI Machine Learning Engineer to lead the development of intelligent agentic systems and drive the evaluation of large language models (LLMs). In this role, you will collaborate with stakeholders to design and implement powerful agents, design robust evaluation frameworks, and contribute to advancing the effectiveness and reliability of AI systems. Responsibilities Build agentic systems tailored to various Software Development Lifecycle (SDLC) personas, translating requirements into actionable implementations Partner closely with cross-functional teams to understand workflows and ensure alignment with stakeholder needs Design and implement robust evaluation test cases for LLMs using LLMs as judges and deterministic methodologies Evaluate model performance and ensure reliability using tools such as LangSmith, LangFuse, or MLFlow Develop and fine-tune prompt frameworks to align LLMs with diverse agent requirements Utilize programming expertise in Python and AI/ML frameworks to enhance agentic systems' capabilities Monitor, debug, and optimize AI systems’ performance using advanced testing and automation practices Leverage modern SDKs like LangGraph or similar frameworks to efficiently build intelligent workflows Foster continuous improvement by incorporating feedback, testing outcomes, and insights into future iterations Act as a thought leader on AI testing standards, governance, and best practices in agentic system development Requirements 3+ years of experience in AI engineering, with emphasis on LLMs and agentic systems Knowledge of modern testing standards and practices applied to agentic systems Strong programming and development skills in Python, with usage of AI/ML frameworks and libraries Familiarity with evaluation and monitoring tools such as LangSmith, LangFuse, or MLFlow Competency in using SDKs like LangGraph or similar frameworks for agentic system development Understanding of LLM concepts, including prompt engineering and fine-tuning methodologies Knowledge of testing frameworks and automation tools for validating AI systems Analytical and problem-solving skills, with a focus on delivering reliable and effective solutions Proficiency in communication and collaboration, ensuring successful teamwork across roles Capability to work independently, delivering high-quality AI solutions in a dynamic environment Excellent written and spoken English (B2+ level) Nice to have Experience writing agentic systems using SDKs like LangGraph or similar technologies Familiarity with evaluation tools such as LangSmith, LangFuse, or MLFlow Understanding of AI governance, safety, and ethical considerations in agentic systems Showcase of enterprise-grade AI solutions with multiple integrations and workflows
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