ML Engineering Lead: Production AI & RAG for LegalTech

Hackajob Ltd; Farringdon; On-site; GBP 85,000 - 115,000; Full time

Job summary

Hackajob Ltd is seeking a Machine Learning Engineering Lead to design, build and operate production ML/LLM-based services, with a focus on reliability and governance. You will own end-to-end ML workflows, including retrieval-augmented generation, embeddings, and semantic search, across legal content use cases.

You will mentor engineers, collaborate with cross-functional teams, drive MLOps, CI/CD, testing, monitoring, and incident response in AWS-hosted environments, while promoting responsible

Qualifications

• Hands-on experience in ML, software or data engineering.
• Experience designing and operating ML/LLM systems in production.
• Experience integrating AI/ML with enterprise systems and data platforms.
• Strong Python development skills for ML and data processing.
• Sound understanding of MLOps, CI/CD, testing, monitoring and observability.

Responsibilities

• Escalation point for AI/ML engineering issues within the area.
• Collaborate with engineers, product stakeholders and platform teams.
• Write and review specifications for complex ML/LLM components.
• Design, build, deploy, and operate production AI/ML services for legal use cases.
• Implement RAG, semantic search, embeddings, and citation-aware capabilities.
• Design agentic workflows and multi-step AI processes with governance.
• Integrate AI/ML with enterprise systems and AWS-hosted services.
• Establish evaluation and quality controls for accuracy and value.

Skills

ML engineering

Software engineering

Data engineering

Python for ML

Cross-functional collaboration

AWS/cloud environments

System design

MLOps

CI/CD

LLM/AI capabilities

Agentic workflows

Observability

Problem solving

Communication

Copilot/Codex

Docker

Kubernetes

Terraform

C#/.NET

SQL Server

Event-driven architecture

LegalTech knowledge

Tools

Docker

Kubernetes

Terraform

GitHub Copilot

Job description

Hackajob Ltd is seeking a Machine Learning Engineering Lead to design, build and operate production ML/LLM-based services, with a focus on reliability and governance. You will own end-to-end ML workflows, including retrieval-augmented generation, embeddings, and semantic search, across legal content use cases.

You will mentor engineers, collaborate with cross-functional teams, drive MLOps, CI/CD, testing, monitoring, and incident response in AWS-hosted environments, while promoting responsible