About the role
Full Stack AI Engineer
Opening: 3
Employment Type: Full Time
Work Experience: 5+ Year(s) To 7 Year(s)
CTC Salary: 12.00 LPA TO 14.00 LPA
Function: IT Software - Web / Mobile
Industry: IT-Software/Software Services
Qualification: B.Tech/B.E. - Computers; BCA/BCS - Computers; M.E./M.Tech - Computers
Location: Ahmedabad, Remote Work Allowed
**Job Description:**Role/Responsibilities
Author precise feature specs covering requirements, edge cases, constraints, and acceptance criteria before any code is written or AI agent is invoked.
Own features end-to-end - translating user outcomes into acceptance criteria, driving development through AI-assisted workflows, and validating output against the spec before delivery.
Design and run generator-critic pipelines - using AI to generate output and a structured critique pass against the same spec to validate it, iterating until acceptance criteria are met.
Build and maintain software components - APIs, data layers, services, and integrations - as the engineering foundation that AI-native workflows operate on top of.
Evaluate and adopt AI tools with structured reasoning - assess new tooling against defined criteria, bring recommendations with evidence, and stay current with the evolving AI development landscape.
Work autonomously across development, quality, and requirements - minimising handoffs through disciplined spec authorship, self-managed validation, and proactive flagging of gaps before building.
Required Skills and Experience
- Bachelor's degree in Software Engineering, Computer Science, or a related technical field.
- 5+ years of overall software development experience, with at least 3 years actively using AI tools as a core part of the development workflow.
- Proficiency in .NET, MS SQL Server (or equivalent RDBMS), MongoDB (or equivalent NoSQL), and API development.
- Ability to write structured, machine-precise specs that serve as ground truth for both code generation and output validation.
- Practical understanding of prompt construction, context engineering, and diagnosing AI output failures.
- Working awareness of the AI tool ecosystem - intelligent system tooling (LLM APIs, RAG, Vector Databases, Agent Frameworks) and SDLC acceleration tooling (Agentic Coding, AI Code Review, AI Test Generation).
- Strong written communication skills and experience working in Agile or Kanban environments with end-to-end ownership of deliverables.
Nice to Have Qualities & Skills
- Hands-on experience building RAG pipelines, working with Vector Databases, or integrating LLM APIs into production systems.
- Experience with multi-agent orchestration frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
- Familiarity with AI observability tooling such as LangSmith, LangFuse, or Braintrust.
- Exposure to spec-driven development practices such as BMAD or GitHub Spec Kit.
- Exposure to Real Estate Technology, Mortgage, or related Financial Services domain.
- Awareness of Model Context Protocol (MCP) and its role in connecting AI agents to external tools and data sources.
Key Skills :
- .net Developer
- Ai Engineer
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