Senior Forward Deployed Engineer (m/f/d)

EPAM Systems; Germany (OH); Hybrid; USD 127,000 - 173,000; Full time

Job summary

EPAM Systems in Germany is seeking a Senior Forward Deployed Engineer to lead the design and deployment of AI-native solutions. You will build end-to-end AI systems using agents, RAG workflows, and robust evaluation frameworks to deliver measurable business value, collaborating with stakeholders to adapt AI tech to real workflows.

The role requires 7+ years in production AI, strong Python, and experience with LangChain, LangGraph, and major cloud platforms.

Qualifications

• ,

Responsibilities

• Build end-to-end AI-native solutions with agents and RAG.
• Design fault-tolerant workflows with retries and human-in-the-loop.
• Translate business needs into scalable AI solutions.
• Write production-grade Python covering APIs and deployments.
• Optimize retrieval and context with vector databases.
• Monitor performance with AI observability tools.

Skills

Python

LLM Systems

Agent design

RAG tech

CI/CD

LangChain

LangGraph

Semantic Kernel

Cloud platforms

German fluency

English fluency

Tools

LangSmith

Arize Phoenix

AWS

Azure

GCP

Vector databases

Job description

We're looking for a Senior Forward Deployed Engineer (m/f/d) to join our team in Germany in a hybrid working mode. In this role, you will design and deliver AI-native solutions where Large Language Models (LLMs) and advanced agentic systems generate real business value. You will work hands-on to build scalable architectures, write production-grade code, and create evaluation frameworks that ensure high performance and reliability. You will collaborate directly with stakeholders and end users to deeply understand their workflows, integrate AI technologies seamlessly into business processes, and improve operations and decision-making. This position demands technical excellence, user-centric problem-solving, and the ability to deliver innovative solutions aligned with client goals.

Responsibilities

• Build AI-native solutions end-to-end, including agents, Retrieval-Augmented Generation (RAG) workflows, tool harnesses and evaluation frameworks
• Design fault-tolerant agent workflows with retries, fallbacks and human-in-the-loop mechanisms to ensure reliability
• Translate business and domain expertise into scalable, repeatable AI solutions
• Write robust production-grade Python code covering APIs, integrations and secure deployment
• Optimize retrieval and context engineering capabilities using vector databases, embeddings and hybrid search
• Develop observability tools with platforms such as LangSmith or Arize Phoenix to monitor performance
• Deploy solutions securely in cloud environments (AWS, Azure or GCP) using containerized deployments and CI/CD pipelines
• Conduct user testing and workflow analysis to validate real-world usability
• Collaborate with cross-functional teams to assess technical feasibility and shape use cases

Requirements

• 7+ years of engineering experience delivering production-grade AI or LLM-based systems
• Expertise in agent design and RAG techniques (vector databases, hybrid search, embedding optimization)
• Advanced proficiency in Python and strong software engineering fundamentals
• Experience with frameworks such as LangChain, LangGraph or Semantic Kernel and familiarity with major LLM providers (OpenAI, Anthropic, Google Gemini)
• Proven ability to design evaluation pipelines and apply AI observability tools
• Hands-on deployment experience with major cloud platforms and CI/CD practices
• Strong communication skills for both technical and non-technical audiences
• Fluency in German and English at C1 level or higher
• Nice to have: Experience with A/B testing and iterative improvements based on usage data
• Background in NLP or applied machine learning, including production deployment
• Knowledge of advanced retrieval methods and enterprise-grade context engineering
• Familiarity with AI governance, compliance, security guardrails and injection prevention
• Exposure to enterprise AI platforms such as AWS Bedrock or Databricks Genie
• Previous work in client-facing or pre-sales consulting roles