About Aedeon
Aedeon is the agent-native modernization platform for the enterprise.
We turn the systems already running the business, applications, databases, data platforms, business rules, and workflows, into governed AI agents, grounded in a persistent Code Intelligence Graph of the customer's own code and verified through behavior-equivalence proof.
Aedeon is delivered as a product, not a services engagement, and runs without mandatory forward-deployed engineers.
As Senior Product Engineer on Aedeon's Agent Systems team, you'll build the agents that do the actual modernization work.
Aedeon's Product Surface Is The Agent Fleet Itself
- parsers that read legacy estates
- extractors that lift business rules out of code
- synthesizers that stand up agentic workflows
- verifiers that produce behavior-equivalence proof
- Agent Systems Development.
- Build and ship specialized agents in the Aedeon fleet: parsers, business-rule extractors, dependency mappers, test synthesizers, behavior replayers, and the orchestration that wires them together.
- Design agents that operate against the Code Intelligence Graph rather than generating from priors, so every agent action traces to a line of code.
- Implement governed autonomy: shadow, supervised, and autonomous stages with human-in-the-loop controls at every stage.
- Orchestrate frontier foundation models (Anthropic, OpenAI, Google) through the Aedeon Decision Model: pick the right model for each task, against the right slice of the graph, under explicit governance constraints.
- Release Ownership.
- Own the full delivery of assigned agents from prototype through deployment and post-release validation.
- Commit to sprint and release deadlines.
- Raise blockers and risks with enough lead time to mitigate them.
- Coordinate with platform and DevOps engineers to keep deployment pipelines clean and repeatable.
- Verification and Quality.
- Practice test-driven development.
- Write the tests for the agent's contract, governance constraints, and equivalence checks before the agent code that satisfies them.
- Build behavior-equivalence verification into every agent: dual-run tests, output diffing, equivalence certificates against production traffic.
- Write detailed test cases before deployment, covering functional flows, edge cases, regression scenarios, and integration touchpoints.
- Use AI tools to generate qualitative test coverage at scale and validate it for completeness.
- Maintain automated test suites (unit, integration, E2E) and integrate them into the CI/CD pipeline.
- Collaboration and Documentation.
- Write clear, maintainable Python with adequate documentation.
- Review pull requests thoroughly and provide constructive feedback.
- Document agent contracts, prompt structures, decision logic, and verification approaches in Confluence or equivalent.
- Share patterns and testing practices across the team.
- Promote a culture of release discipline and quality.
What are we looking for :
- Core Python and Systems.
- Strong Python (4+ years production), async (asyncio), performance optimization, idiomatic code.
- Solid grasp of distributed systems concepts: state machines, retries, idempotency, eventual consistency.
- Experience integrating with LLM APIs (Anthropic, OpenAI, or similar) from production code: streaming, function calling, structured output, retries, prompt management.
- Comfort with FastAPI or equivalent async web frameworks.
- Cloud and Infrastructure.
- Working knowledge of AWS services: EKS, ECS Fargate, S3, DynamoDB, Lambda, Secrets Manager, CloudWatch.
- Experience with Docker and Kubernetes: writing Dockerfiles, Helm charts, and Kubernetes manifests.
- Comfort with CI/CD pipelines, GitHub Actions preferred.
- Comfort navigating multi-account AWS environments (dev, uat, prod).
- Testing and Automation.
- Test-driven development as a discipline.
- Tests written before the code, not after.
- Hands-on experience with pytest, integration testing, and E2E testing.
- Ability to design behavior-verification harnesses: dual-run, output comparison, equivalence proof.
- Experience using AI tools (Claude, Copilot, LLM-based test generators) to accelerate and improve test case quality.
- Experience integrating automated tests into CI/CD pipelines.
- Engineering Mindset.
- Test-first, release-disciplined, ownership-driven.
- Strong written and spoken English.
- You'll be in product reviews and customer-impacting design discussions.
- Available to work with US business-hour overlap from India.
You'll Be Preferred If
- Agentic AI frameworks: AWS Bedrock AgentCore, Strands SDK, LangChain, or similar.
- Temporal.io or other workflow orchestration engines.
- Graph databases (Neo4j) and Cypher query language.
- Amazon OpenSearch Service or Elasticsearch.
- Java exposure for working with the Java Analyzer component.
- Prior B2B SaaS product work with a structured release process.
- Domain exposure to enterprise modernization: mainframe, SAP, Oracle, or large Java / .NET estates.
(ref:hirist.tech)
