Roles and 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.

Requirements:

- 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)