Senior Software Engineer - AI/ML

Mitratech; München; Vor Ort; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

Mitratech is seeking a Senior Software Engineer specializing in Generative AI and Large Language Models to join our team. You will architect and deliver production‑grade AI solutions for complex business objectives, with a focus on agentic systems, retrieval augmented generation, and rigorous evaluation.

The ideal candidate brings hands‑on experience building multi‑agent pipelines, end‑to‑end RAG, model evaluation, and scalable AI infrastructure on AWS.

Qualifikationen

• Production experience designing multi‑agent systems with tool use, memory/state management, and fault‑tolerant routing.
• RAG pipelines end‑to‑end: chunking, embedding models, vector databases, retrieval tuning, and end‑to-end answer synthesis.
• Experience defining and running evaluation pipelines for generative AI — automated scoring, human evaluation design, hallucination mitigation, and drift monitoring.
• Hands‑on with foundation models and GenAI providers (AWS Bedrock, OpenAI, Anthropic, Meta).
• Strong grounding in classical NLP techniques and knowing when to apply them with or without LLMS.
• Experience with Bedrock, SageMaker, Lambda, OpenSearch, IAM, CloudWatch, VPC.
• Terraform or AWS CDK for IaC and reproducible provisioning.
• Production‑quality Python: packaging, testing, type hints, async, ML pipelines.
• Familiarity with ML frameworks and fine‑tuning workflows.
• Langfuse, Arize or Langsmith for experiment tracking.
• Ability to translate ambiguous goals into concrete tech solutions and communicate tradeoffs.
• Strong collaboration across engineering, product, and data teams.
• Rigorous, evidence‑driven mindset; ship with confidence.

Aufgaben

• Design, build, and operate multi‑agent workflows with orchestration, state management, safety guardrails, and fallback strategies.
• Architect and maintain end‑to‑end RAG systems: ingestion, chunking, embedding, vector retrieval, reranking, and answer synthesis.
• Evaluate and integrate LLMs/GenAI services: cost, performance, privacy, and model mix.
• Develop prompting strategies; implement automated prompt testing and regression tracking.
• Define evaluation frameworks for generative outputs: automated metrics, human eval, drift monitoring.
• Apply classical NLP techniques where appropriate in production.
• Build scalable, secure AI infrastructure on AWS following IaC.
• Own CI/CD for models and agents, testing, observability, and rollback.
• Ensure data quality via validation and augmentation.

Kenntnisse

Agent Orchestration

RAG & Retrieval

Evaluations

LLMs & GenAI

Traditional NLP

AWS Bedrock

AWS Ecosystem

MLOps & CI/CD

Infrastructure as Code

Python

ML Frameworks

Experiment Tracking

Cross-functional Collaboration

Ausbildung

Master’s degree in ML/CS (NLP)

Tools

LangChain

LangGraph

AutoGen

Bedrock Agents

Knowledge Bases

Guardrails

SageMaker

OpenSearch

Terraform

AWS CDK

Langfuse

Arize

Langsmith

Jobbeschreibung

At Mitratech, we are a team of technocrats focused on building world‑class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading‑edge technologies available.

For over 35 years, the experts at Mitratech have been focused on solving complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries.

As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work!

Given our continued growth, we always have room for more intellect, energy, and enthusiasm - join our global team and see why it's so special to be a part of Mitratech!

Job Overview

We are seeking a highly skilled Senior Software Engineer specialising in Generative AI and Large Language Models, with a strong focus on agentic systems, Retrieval‑Augmented Generation, and AI evaluations, to join our dynamic team. The ideal candidate will play a pivotal role in architecting and delivering production‑grade AI solutions that meet complex business objectives effectively. This position requires a blend of expertise in modern AI technologies and software engineering, along with a passion for staying at the forefront of advancements.

Essential Duties & Responsibilities

• Design, build, and operate multi‑agent workflows and tool‑enabled agents, implementing orchestration logic, state management, safety guardrails, and fallback strategies for resilient production pipelines.
• Architect and maintain end‑to‑end RAG systems, covering document ingestion, chunking, embedding, vector retrieval, reranking, and answer synthesis with a focus on quality, attribution, and latency.
• Evaluate and integrate LLMs and GenAI services across cost, performance, and privacy dimensions, selecting the right mix of managed and in‑house models.
• Develop, version, and optimise prompting strategies; implement automated prompt testing and regression tracking to maintain output quality and reliability.
• Define and own evaluation frameworks for generative outputs, including automated metrics, LLM‑as‑judge approaches, human evaluation protocols, hallucination detection, and drift monitoring.
• Apply classical NLP techniques where appropriate and maintain awareness of data distribution shifts that could impact model behaviour in production.
• Build and operate scalable, secure AI infrastructure on AWS (Bedrock, SageMaker, Lambda, OpenSearch), following well architected principles and infrastructure‑as‑code practices.
• Own the full deployment lifecycle: CI/CD for models and agents, testing strategies, observability, and rollback procedures.
• Ensure data quality through rigorous validation and augmentation, and proactively source datasets for training, fine‑tuning, and evaluation.

Requirements & Skills

• Agent Orchestration: Production experience designing multi‑agent systems with tool use, memory/state management, and fault‑tolerant routing. Familiarity with LangChain, LangGraph, AutoGen, or custom orchestrators.
• RAG & Retrieval: Hands‑on experience building RAG pipelines end‑to‑end: chunking, embedding models, vector databases, retrieval tuning, and answer synthesis at production scale.
• Evaluations: Strong experience defining and running evaluation pipelines for generative AI — automated scoring, human evaluation design, hallucination mitigation, and drift monitoring. LLM‑as‑judge patterns are a plus.
• LLMs & GenAI: Demonstrated experience with foundation models and GenAI providers (AWS Bedrock, OpenAI, Anthropic, Meta). Comfortable with fine‑tuning, instruction tuning, and prompt engineering at scale.
• Traditional NLP: Solid grounding in classical NLP techniques (NER, text classification, intent detection, topic modelling) and good judgement on when to apply them alongside or instead of LLMs.
• AWS Bedrock: Hands‑on experience with Amazon Bedrock: foundation model APIs, Bedrock Agents, Knowledge Bases, and Guardrails. Experience with Bedrock Model Evaluation is a plus.
• AWS Ecosystem: Proficiency with SageMaker, Lambda, ECS/EKS, S3, OpenSearch, IAM, CloudWatch, and VPC networking.
• MLOps & CI/CD: Familiarity with model registries, CI/CD for ML, feature stores, canary deployments, monitoring, and rollback.
• IaC: Experience with Terraform or AWS CDK for reproducible infrastructure provisioning.
• Python: Production‑quality Python: packaging, testing (pytest), type hints, async programming, and clean ML pipeline abstractions.
• ML Frameworks: Familiarity with traditional ML frameworks and fine‑tuning workflows.
• Experiment Tracking: Experience with Langfuse, Arize or Langsmith, or equivalent for tracking runs, metrics, and artefacts.
• Ability to translate ambiguous business goals into concrete technical solutions and communicate tradeoffs to non‑technical stakeholders.
• Strong collaborative instincts — comfortable working across engineering, product, and data teams.
• A rigorous, evidence‑driven mindset: you ship with confidence because you measure, test, and monitor thoroughly.

Education

• A Master’s degree in Machine Learning, Computer Science with a preference for specialization in the NLP domain.

We are an equal‑opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.