Software Engineer - Applied AI

San Franciscofull timeOn Site

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mid

$180k–$480k

H1B: no

Titan Msp The Software Engineer - Applied AI at Titan Msp owns the systems that make AI agents work in production, building integrations, APIs, and backend infrastructure. The role involves prototyping solutions from ill-defined problems and collaborating with partners and internal teams to drive adoption and business outcomes.

Responsibilities

As an Applied AI Software Engineer, you own the systems that make Titan's agents work in production. You're as effective in front of a partner as you are deep in the codebase, and you move between the two every week.
You take ill-defined problems from the field, prototype quickly, and turn them into reliable production systems. You'll build the agent harness, ship new capabilities across the portfolio, and own the backend systems, data pipelines, and model-adjacent infrastructure underneath them. You work closely with other engineers, Operations, Product, and GTM.
This role is based in San Francisco or New York City, in office.
Embed with portfolio teams to understand their technical requirements and business objectives
Architect and build integrations, APIs, and agent workflows on Titan's platform
Build and evolve the agent harness and tools our AI agents run on
Work with partner leadership to drive adoption and shape business outcomes across the portfolio
Build the platform and software systems that scale future deployments
Design evals that measure agent quality, then hill-climb our agents against them
You might thrive in this role if you
Bring 3+ years of engineering experience that includes partner-facing work
Write and review production-grade code in TypeScript, Python, or a comparable stack

Qualification

experience in IT operationsexperience in MSPsexperience in infosec

Required

3+ years of engineering experience that includes partner-facing work
Write and review production-grade code in TypeScript, Python, or a comparable stack
Have built LLM applications or agents in production
Have built full-stack systems end to end, with strong fundamentals in backend services, data modeling, and reliability
Have owned and shipped complex systems in ambiguous, fast-moving environments
Communicate clearly with partner stakeholders, engineers, and product managers