Lead Ai Engineer

Role & responsibilities

• Leading, mentoring, and managing a team of AI Engineers - setting technical direction, reviewing architecture and code, and supporting their day-to-day growth.
• Driving the architecture of Tristone's agentic AI platform end to end, spanning agents, MCP servers, and supporting services that propose and apply changes across large codebases and financial workflows.
• Designing and overseeing retrieval systems (RAG, vector search, hybrid approaches) that give AI agents and developers accurate, up-to-date context from large codebases, financial documents, and design artifacts.
• Building and refining compile, test, and evaluation pipelines, covering static analysis, style and safety checks, performance gates, and code review, to consistently measure and raise the quality of AI-generated changes.
• Defining best practices around concurrency, telemetry, configuration hygiene, prompt versioning, and performance-sensitive code paths, so AI outputs remain reliable and idiomatic.
• Driving experiments and evaluation frameworks to continuously improve AI-driven workflows across the team.
• Acting as the primary point of technical escalation for the AI engineering function, liaising with the MD and cross-functional stakeholders on priorities, timelines, and risk.
• Complying with IT policies and procedures.
• Maintaining security of information at all times.

Preferred candidate profile

• 4+ years of overall engineering experience, including demonstrable experience building and shipping AI/LLM-powered systems.
• Prior experience leading, mentoring, or managing engineers, or clear readiness to step into a team-lead role.
• Strong proficiency in Python (Java a plus), with hands-on experience in production-grade software systems.
• Proven experience with agentic AI frameworks and patterns (LangChain, LangGraph, AutoGen, CrewAI, or similar) and multi-agent orchestration.
• Practical experience with retrieval systems - vector search, embeddings, RAG pipelines, or hybrid retrieval approaches.
• Experience with MCP (Model Context Protocol) servers or comparable tool/agent-integration architectures.
• Strong communication skills, with the ability to translate technical decisions for non-technical stakeholders and senior leadership.
• Comfort operating in a fast-paced, high-trust environment handling sensitive financial data.

Strong preferred

• Experience in fintech, financial services, or investment/deal-related domains (M&A, private equity, IPO due diligence, or similar).
• Familiarity with compiler/static analysis tools or large-scale refactoring systems.
• Experience fine-tuning or customizing open-weight models.
• Knowledge of model-serving infrastructure and evaluation/observability tooling for LLM systems.
• Exposure to security-conscious deployment practices (OWASP LLM Top 10, API hardening, audit logging).

Qualification

• Bachelors or Masters in Computer Science (or related) with strong fundamentals (algorithms, data structures, systems)