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Location
In office (Bengaluru)
Employment
Full-Time

First seen by Alion on Oct 30, 2026.

Overview
Company
Impact
Profile match
Sonata Software is an Indian IT services and technology company headquartered in Bengaluru that provides modernization engineering across cloud, data, AI, Microsoft Dynamics, test automation and managed services. Founded in 1986 and listed in India, it runs the Harmoni.AI enterprise platform and works with Fortune 500 clients in banking, retail, healthcare, manufacturing and technology, with a presence in the US, UK, Malaysia, Mexico, Australia, the DACH region and the Nordics. It hires data and cloud architects, MLOps and DevOps engineers, .NET and full-stack developers, identity and security specialists, SharePoint administrators and JD Edwards consultants.

Key Responsibilities

  • Translate business requirements into clear, structured specifications that drive AI-assisted design, code generation, and test creation.
  • Build high-performance backend services and APIs in Go using AI agents within an AI SDLC workflow.
  • Develop responsive, modular frontend applications in Angular, integrating seamlessly with backend APIs.
  • Design, optimize, and maintain PostgreSQL schemas, queries, indexes, and stored procedures.
  • Review, validate, and refine AI-generated code for correctness, security, and performance.
  • Build and maintain prompt libraries, agent workflows, and spec templates as reusable SDLC assets.
  • Leverage AI to automate unit, integration, and regression testing, and to keep documentation aligned with code.
  • Collaborate with architects, QA, and product owners in an agile, spec-first delivery model.

Required Skills

  • AI SDLC: proven, daily use of AI tools across the full development lifecycle, beyond code completion.
  • Go: experience building production-grade services, with strong command of concurrency.
  • Angular: hands-on experience with components, services, routing, and state management.
  • PostgreSQL & SQL: data modeling, performance tuning, and database migrations.
  • Spec Driven Development: writing precise, testable specifications that AI agents can implement and verify.
  • Prompt and context engineering: structuring prompts, context, and instructions to produce reliable AI output.
  • Critical judgment: ability to identify hallucinations, security gaps, and logic errors in AI-generated work.
  • Tooling: Git, Bitbucket, Jira, Confluence, GitHub Copilot, and CI/CD pipelines.

Good to Have

  • Experience with agentic frameworks, MCP (Model Context Protocol), or LLM APIs.
  • Exposure to legacy-to-modern data platform migration.
  • Prior delivery experience on an end-to-end AI SDLC project using Spec Driven Development.
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