Software Engineer

The Role

We are hiring Senior Software Engineers and Software Engineering Leads who have completed the full SDLC the AI-native way — where agentic tools are core contributors, not assistants. You will own delivery end-to-end, work directly with enterprise customers, and contribute to Aivar's accelerator platforms across regulated industries.

What You'll Do

• Own end-to-end delivery using spec-driven agentic workflows — Requirements → Design → Tasks → Implementation → Deployment
• Build and contribute to Convogent, Velogent, and Kubogent accelerator platforms
• Lead agile delivery including sprint planning, backlog grooming, and stakeholder reporting on client-facing engagements
• Manage distributed delivery teams within fixed-price, milestone-gated engagements (Lead level)
• Design and implement Amazon Bedrock Knowledge Bases and RAG retrieval pipelines for enterprise customers
• Build MCP connectors integrating requirements, GitLab, and enterprise tools into the AI-native pipeline
• Implement verification & validation hooks and automated traceability gates in regulated software pipelines
• Ingest compliance and regulatory documents — DHF, traceability matrices, V&V protocols — into knowledge bases and RAG systems
• Build developer hooks — lint, type-check, security scanning — wired into CI/CD pipelines
• Mentor and guide engineers on AI-native engineering practices (Lead level)

What We're Looking For

Experience

• 5+ years in software development across the full SDLC
• 1+ year of end-to-end AI SDLC experience — shipped in production, not just explored
• Experience delivering on client-facing consulting engagements in regulated industries (fintech, healthcare, life sciences, or manufacturing) preferred

AI-Native Tooling — hands-on with 2 or more, used in production:

• Amazon Kiro, Claude Code, Codex, Cursor, GitHub Copilot, Google Gemini

Technical Skills

• Proficient in Python, TypeScript, Java, or Go
• Hands-on with AWS — Bedrock, Knowledge Bases, Agents, Lambda, EKS
• Experience with microservices, REST APIs, and GitLab / CI/CD pipelines
• Understanding of LLMs, RAG, prompt engineering, and agentic system design
• Familiarity with MCP (Model Context Protocol) connector development
• Exposure to regulated software pipelines with V&V, traceability, and compliance requirements is a strong plus

You're a Strong Fit If

• You have authored steering files and spec documents as part of an AI-native SDLC
• You have built or configured Amazon Bedrock RAG pipelines end-to-end
• You have delivered a complete feature or module autonomously using an AI coding agent
• You have worked with compliance or regulatory document ingestion into knowledge bases
• You understand the real challenges of AI-native delivery — context management, agent failure modes, hallucinations — and have strategies to handle them