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# Fullstack Software Engineer, ADK

- **Company:** PELICO
- **Location:** Boston, MA, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software as a Service, Data Streaming, ReactJS, Large Language Models, Multi-Agent Systems, Backend, Front End Software Development
- **Published:** July 22, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=e5bea59538db598a

## About the Role

We care about how good you are and how far you can go, and we calibrate to the experience you bring. This seat is built for exceptional people - whether you are just out of a top program or already have a few years of serious building behind you.

 * An excellent engineer who ships. You write excellent code and have built real things, full-stack across a Python backend and a React frontend - or you are clearly able to get there fast.
 * Hungry and driven. You want a hard problem to own, not a comfortable seat, and you have the ceiling to grow into far more.
 * Rigorous with non-deterministic systems. You spec and eval before shipping, trust evidence over vibes, and own what goes out - including AI-assisted code - following problems into production.
 * AI-native and curious. You understand how agent frameworks, tools, and evals actually work under the hood, and you build with AI coding tools every day.
 * Calm in fast-moving ambiguity. You stay effective on a stack where this quarter's best practice changes next quarter, turning uncertainty into a workable plan.

Nice to have: real AI/agent product experience (MCP, agent frameworks, evals); durable workflow engines (e.g. Temporal); streaming UIs; observability (OpenTelemetry); spec-driven development; multi-tenant SaaS, or aerospace/defense/discrete-manufacturing context.

## Description

* Ship agent capabilities end to end. Build real features from the tool/MCP and orchestration backend through to the React console, live for users - not demos.
 * Harden the runtime. Durable execution, retries, scheduling, and human-in-the-loop approvals on agent actions that carry real consequences.
 * Make agents trustworthy. Grow the eval harness (scenario evals, LLM-as-judge) so we catch regressions in agent behavior before they ship.
 * Build a console people believe. Real-time streaming of agent events, tool calls, and approvals - clear, fast, and reliable enough that a controller trusts it.
 * Set a craft bar. Write specs others build against, keep the frontend/backend contract honest, and leave reusable patterns the team adopts.


## Related Videos

- [Python-Based Data Streaming Pipelines Within Minutes](https://www.wearedevelopers.com/videos/1233-python-based-data-streaming-pipelines-within-minutes)
- [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock)
- [Watch Tests Go Brrrr! : Getting Started with Cypress in ReactJS](https://www.wearedevelopers.com/videos/282-watch-tests-go-brrrr-getting-started-with-cypress-in-reactjs)
- [The AI-Ready Stack: Rethinking the Engineering Org of the Future](https://www.wearedevelopers.com/videos/1706-the-ai-ready-stack-rethinking-the-engineering-org-of-the-future)
- [Why and when should we consider Stream Processing frameworks in our solutions](https://www.wearedevelopers.com/videos/1085-why-and-when-should-we-consider-stream-processing-frameworks-in-our-solutions)
- [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean)

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