Lead Ai Engineer

·         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.

Strongly 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-

• Bachelor’s or Master’s in Computer
  Science (or related) with strong fundamentals (algorithms, data
  structures, systems)