Staff Software Engineer - AI Platform

Greybridge Search & Selection; New York (NY); On-site; USD 150,000 - 190,000; Full time

Job summary

Greybridge Search & Selection is seeking a hands-on Staff Software Engineer to shape backend and AI platform powering AI-native products. This high-ownership role puts you close to code while setting technical direction across a team.

You'll work on systems behind production AI agents, conversations, knowledge bases and complex workflows, building scalable services in Python, FastAPI, PostgreSQL and AWS. Mentor teammates and drive reliability at scale.

Qualifications

• 5-7+ years of software engineering experience building scalable cloud applications and APIs.
• Hands-on Python experience, ideally with FastAPI.
• Experience with AI/LLM-powered products or platforms.
• Production experience with AWS and relational databases.

Responsibilities

• Lead large, multi-quarter technical initiatives across AI, product and infrastructure.
• Design and build backend services and distributed systems.
• Develop AI orchestration involving LLMs, agents, tool calling, MCP and multi-step workflows.
• Establish observability, testing, reliability and incident response.
• Mentor engineers and influence technical direction.

Skills

Python

FastAPI

PostgreSQL

AWS

Distributed systems

APIs

AI/LLM

Observability

Mentoring

Code review

Job description

Location: Brooklyn, Frisco, Eagan, Toronto, or Ann Arbor

Level: Staff / Lead Software Engineer

We’re working with a leading technology company building AI-native products that are changing how professionals work with complex, document-heavy information.

We’re looking for a hands-on Staff Software Engineer to help shape the backend and AI platform powering these products. This is a high-ownership role for an engineer who enjoys being close to the code while also setting technical direction across a team.

The role

You’ll work on the systems behind production AI agents, conversations, knowledge bases and complex workflows. You’ll help define how AI capabilities are built, integrated and operated reliably at scale.

You’ll have the opportunity to:

• Lead large, multi-quarter technical initiatives across AI, product and infrastructure
• Design and build backend services and distributed systems using Python, FastAPI, PostgreSQL and AWS
• Build AI orchestration involving LLMs, agents, tool calling, MCP and multi-step workflows
• Develop retrieval, search, vector and document-processing capabilities
• Design for high-throughput, low-latency AI workloads, including caching, queuing, rate limiting and model failover
• Establish strong approaches to observability, testing, reliability and incident response
• Mentor engineers and influence technical direction across the wider organisation
• Work closely with product, ML and research teams to turn emerging AI capabilities into reliable production systems

You’ll ideally have:

• 5-7+ years of software engineering experience building scalable cloud applications and APIs
• Strong, recent hands-on Python experience, ideally with FastAPI or similar frameworks
• Strong knowledge of distributed systems, backend architecture, APIs, databases and cloud infrastructure
• Production experience with AWS and relational databases such as PostgreSQL
• A track record of owning complex engineering projects from architecture through to production
• Experience building or integrating AI/LLM-powered products or platforms
• Exposure to agents, tool calling, MCP, RAG, retrieval, embeddings or vector search
• Strong understanding of production reliability, observability, testing and performance
• The ability to influence technical direction while remaining highly hands-on

Experience in environments where correctness, auditability or compliance matter is useful, but not essential.

This is a chance to join a small, highly experienced engineering team with a significant technical surface area and the backing of an established global technology organisation.

You’ll have genuine ownership over how AI systems are architected and built, with the opportunity to influence engineering practices beyond a single product or feature.

If you're a Staff-level engineer who enjoys building AI systems from the ground up - and still wants to be deep in the code - we'd be interested in speaking with you.