Senior Software Engineer – AI/ML

About Mitratech

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 supporting individual excellence and takes pride in our 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 us 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 more than 160 countries.

As we continue to grow, we’re always looking for resourceful, enthusiastic individuals with fresh perspectives. Given our continued growth, we always have room for more intellect, energy, and enthusiasm. Join our global team and discover what makes Mitratech a truly exceptional place to work!

Job Overview

We are seeking a highly skilled Senior Software Engineer specializing in Generative AI and Large Language Models (LLMs), with a strong focus on agentic systems, Retrieval-Augmented Generation (RAG), 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 effectively meet complex business objectives. This position requires a combination of expertise in modern AI technologies and software engineering, along with a passion for staying at the forefront of technological advancements.

Essential Duties & Responsibilities

• Agentic Systems and Orchestration: 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.
• Retrieval-Augmented Generation (RAG): 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.
• LLM and GenAI Integration: Evaluate and integrate LLMs and GenAI services across cost, performance, and privacy dimensions, selecting the right combination of managed and in-house models.
• Prompt Engineering: Develop, version, and optimize prompting strategies. Implement automated prompt testing and regression tracking to maintain output quality and reliability.
• AI Evaluation Frameworks: Define and own evaluation frameworks for generative outputs, including automated metrics, LLM-as-judge approaches, human evaluation protocols, hallucination detection, and drift monitoring.
• Natural Language Processing (NLP): Apply classical NLP techniques where appropriate and maintain awareness of data distribution shifts that could impact model behavior in production.
• AI Infrastructure on AWS: Build and operate scalable, secure AI infrastructure using AWS services such as Bedrock, SageMaker, Lambda, and OpenSearch, following well-architected principles and infrastructure-as-code practices.
• Deployment and Operations: Own the full deployment lifecycle, including CI/CD for models and agents, testing strategies, observability, and rollback procedures.
• Data Quality and Datasets: 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 and state management, and fault-tolerant routing. Familiarity with LangChain, LangGraph, AutoGen, or custom orchestrators.
• RAG and Retrieval: Hands-on experience building end-to-end RAG pipelines, including chunking, embedding models, vector databases, retrieval tuning, and answer synthesis at production scale.
• AI Evaluations: Strong experience defining and running evaluation pipelines for generative AI, including automated scoring, human evaluation design, hallucination mitigation, and drift monitoring. Familiarity with LLM-as-judge patterns is a plus.
• LLMs and Generative AI: Demonstrated experience with foundation models and GenAI providers such as AWS Bedrock, OpenAI, Anthropic, and Meta. Comfortable with fine-tuning, instruction tuning, and prompt engineering at scale.
• Traditional NLP: Solid grounding in classical NLP techniques, including named entity recognition (NER), text classification, intent detection, and topic modeling, with good judgment on when to apply them alongside or instead of LLMs.
• AWS Bedrock: Hands-on experience with Amazon Bedrock, including 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 and CI/CD: Familiarity with model registries, CI/CD for machine learning, feature stores, canary deployments, monitoring, and rollback procedures.
• Infrastructure as Code (IaC): Experience with Terraform or AWS CDK for reproducible infrastructure provisioning.
• Python Development: Production-quality Python skills, including packaging, testing with pytest, type hints, asynchronous programming, and clean ML pipeline abstractions.
• Machine Learning Frameworks: Familiarity with traditional machine learning frameworks and fine-tuning workflows.
• Experiment Tracking and Observability: Experience with Langfuse, Arize, LangSmith, or equivalent tools for tracking runs, metrics, and artifacts.
• Business and Technical Communication: Ability to translate ambiguous business goals into concrete technical solutions and communicate trade-offs to non-technical stakeholders.
• Collaboration: Strong collaborative instincts and comfort working across engineering, product, and data teams.
• Evidence-Driven Mindset: A rigorous, evidence-driven approach to delivering reliable solutions through thorough measurement, testing, and monitoring.

Education

• Master’s Degree: A Master’s degree in Machine Learning or Computer Science, preferably with a specialization in Natural Language Processing (NLP).

Equal Opportunity Statement

Mitratech is 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.