·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)