SSE.Net Developer - AI

About Kadel Labs

Kadel Labs is a deep-tech IT services company dedicated to
transforming businesses with cutting-edge solutions. Our expertise spans Data
Analytics, Engineering, and Visualization; Cloud services including DevOps,
InfoSecOps, and InfraOps; Software development and modernization; and
Generative AI-driven business applications. As a trusted partner of DataBricks,
Azure, AWS, Web Methods, and Bitrix24 CRM, we empower businesses with
innovative, reliable, and scalable technology solutions.

Job Title: SSE-.NET AI Engineer

About the Role

We are seeking a SSE-.NET AI Engineer who can own
features end-to-end, combining strong software engineering fundamentals with
AI-native development practices. The role involves translating user outcomes
into precise specifications, driving development through AI-assisted workflows,
building scalable software components, and validating solutions against defined
acceptance criteria.

Key Responsibilities

Feature & Requirements Ownership

• Author
  precise feature specifications covering requirements, edge cases,
  constraints, and acceptance criteria before development begins.
  
• Own
  features end-to-end by translating user outcomes into clear acceptance
  criteria.
  
• Drive
  development through AI-assisted workflows and validate outputs against
  defined specifications before delivery.
  
• Proactively
  identify and flag gaps or ambiguities before development begins.
  

AI-Native Engineering

• Design
  and run generator-critic pipelines, using AI to generate outputs
  followed by structured critique against the same specification.
  
• Iterate
  on AI-generated outputs until defined acceptance criteria are met.
  
• Evaluate
  and adopt AI tools using structured reasoning and defined evaluation
  criteria.
  
• Stay
  current with the evolving AI development and tooling landscape.
  

Software Development

• Build
  and maintain software components including APIs, data layers, services,
  and integrations.
  
• Develop
  and maintain the engineering foundation that supports AI-native workflows.
  
• Work
  autonomously across development, quality, and requirements while
  minimising unnecessary handoffs.
  
• Ensure
  disciplined specification, self-managed validation, and end-to-end
  ownership of deliverables.
  

Required Skills & 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 of 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.
  
• Strong
  ability to write structured, machine-precise specifications 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, including:
  
• LLM
  APIs
  
• RAG
  
• Vector
  databases
  
• Agent
  frameworks
  
• Agentic
  coding
  
• AI
  code review
  
• AI
  test generation
  
• Strong
  written communication skills.
  
• Experience
  working in Agile or Kanban environments with end-to-end ownership
  of deliverables.
  

Nice to Have

• 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 tools 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
  domains.
  
• Awareness
  of Model Context Protocol (MCP) and its role in connecting AI
  agents to external tools and data sources.
  

Why Join Kadel Labs

• Opportunity
  to work on AI-native software development and modern engineering
  practices.
  
• Work
  with emerging AI technologies, tools, and agentic development frameworks.
  
• Opportunity
  to own features end-to-end and directly influence product outcomes.
  
• Collaborative
  and growth-oriented work environment.
  
• Opportunity
  to work on innovative solutions across software engineering