Senior Software Engineer - AI/ML

Mitratech; Germany (OH); Hybrid; USD 100,000 - 140,000; Full time

Benefits offered by this job

Equal opportunity employer policy

Job summary

Mitratech is seeking a highly skilled Senior Software Engineer specializing in Generative AI and Large Language Models. You will be pivotal in architecting production-grade AI solutions and building multi-agent workflows.

Applicants should have strong expertise in modern AI technologies, extensive experience with RAG pipelines, and familiarity with tools like AWS Bedrock and LangChain. A Master’s degree in a relevant field is required. Join us in pushing the boundaries of AI technology.

Qualifications

• Experience designing multi-agent systems, familiarity with orchestration tools.
• Hands-on experience building RAG pipelines.
• Strong experience with generative AI evaluations.
• Experience with foundation models in AWS ecosystem.
• Proficiency in production-quality Python and ML frameworks.

Responsibilities

• Design and build multi-agent workflows.
• Maintain and optimize end-to-end RAG systems.
• Integrate LLMs and GenAI services.
• Develop and version prompting strategies.
• Define evaluation frameworks for generative outputs.

Skills

Agent Orchestration

RAG & Retrieval

Evaluations

LLMs & GenAI

Traditional NLP

AWS Bedrock

AWS Ecosystem

MLOps & CI/CD

IaC

Python

ML Frameworks

Experiment Tracking

Education

Master’s degree in Machine Learning or Computer Science with NLP specialization

Tools

AWS

LangChain

Terraform

OpenAI

Langfuse

Job description

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.

• 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.