Senior Software Developer (AI Agents)

ABOUT THE ROLE

The Data + Automation team at nCircle Tech builds the data and automation infrastructure behind decision

making across the business. Our platform runs on Databricks and AWS. We're hiring a strong software

engineer to design, build, and ship production services - including LLM-powered agents and the tooling

around them. This is a hands-on, code-first role.

WHAT YOU'LL WORK ON

• Designing, building, and productionizing LLM agents: tool-use loops, retrieval, orchestration,

evaluation, and guardrails

• Writing the production-grade services and APIs around those agents in Python and Node/TypeScript
• Deploying and operating on AWS - provisioning with IaC, wiring CI/CD, owning your code from

commit to production

• Contributing to a shared codebase with feature branches, code review, and Conventional Commits

REQUIRED

Software Engineering (the core)

• Strong Python and Node/TypeScript - writes clean, tested, production-grade code, not scripts
• Solid fundamentals: data structures, API design, error handling, testing, debugging real systems
• Feature branches and PRs; comfortable both giving and receiving code review; meaningful commit

messages

• Follows engineering standards (12-factor, testing, documentation) without hand-holding

AWS + IaC

• Real AWS experience - the environment our services run on
• Deploys with Infrastructure as Code (Terraform, CDK, or equivalent) rather than clicking through

consoles

• Comfortable with CI/CD, environment promotion, and AWS basics (S3, IAM, networking)

LLM Agents (non-negotiable)

This is a hard requirement, not a nice-to-have. We are a small team and cannot train this skill on the job

- you must already know how to build agents and be able to contribute to real work quickly.

• Has built and shipped LLM agents to production - not demos or prototypes; systems that ran and

were relied on

• Can explain the agent loop from experience: how the model decides to call a tool, observes the result,

and re-decides across multiple steps

1

Senior Software Engineer, AI Agents

• Has designed retrieval (RAG) end-to-end - chunking, indexing, hybrid or re-ranked retrieval - and

can justify each choice

• Has a real evaluation story: how they measured whether the agent was correct, and the worst failure

mode they hit in production and fixed

• Knows when NOT to use an agent - where a plain LLM call or deterministic code is the better answer
• Framework-agnostic - LangChain, CrewAI, Databricks Agent Framework, or raw tool-use loops all

fine; what matters is that you've shipped real agents

Databricks (working proficiency)

Our platform runs on Databricks, so this is required - but working proficiency, not mastery. You should

be able to build and ship in Databricks unaided; you don't need to be a Spark-tuning specialist.

• Comfortable building and running Databricks notebooks and Jobs (task chains, parameters,

schedules) end-to-end

• Understands the Unity Catalog three-part namespace (catalog.schema.table) and works within it
• Has written Delta Lake operations beyond basic reads - e.g. MERGE, overwrite, schema evolution
• Can navigate and debug an existing pipeline, not only write greenfield code

GOOD TO HAVE

• Deeper Databricks / Spark depth - performance tuning, advanced Unity Catalog governance
• MCP (Model Context Protocol) exposure
• Agent observability and tracing tools in production
• Construction, AEC, or project-based industry experience
• Jira

GENERAL BAR

• 5+ years writing code, not configuring tools
• Ships independently: scopes work, executes, communicates progress
• Can ramp on an unfamiliar system by reading docs and asking targeted questions