Software Engineer - AI Platform

Accountabilities:

• • Own the full software development lifecycle, including application design, API development, implementation, deployment, monitoring, and ongoing improvements.
  • Build application services and business logic that connect AI capabilities with relational database operations and enterprise data workflows.
  • Integrate AI agent frameworks such as LangChain and modern interoperability protocols such as MCP and A2A into production applications.
  • Design secure, versioned data models supporting multi-tenant isolation, auditability, data classification, and reliable data management.
  • Develop and maintain services that operate consistently across AWS, Azure, GCP, and on-premises environments using automated CI/CD pipelines.
  • Improve application performance through SQL and query optimization, profiling, caching, security practices, and feature-level performance targets.
  • Design and implement REST and/or gRPC APIs for external consumers and frontend applications.
  • Establish effective observability through structured logging, distributed tracing, monitoring, and functional alerting.
  • Participate in technical design and code reviews, mentor teammates, and make pragmatic engineering decisions within an async-first environment.
  • Maintain end-to-end ownership of meaningful system components while collaborating directly with product stakeholders and customers.

  Requirements

  • 5+ years of professional software development experience, including at least 2 years working with data-intensive applications, database-adjacent functionality, or enterprise software.
  • Proven experience taking substantial production features from functional specification through implementation, deployment, and ongoing operation.
  • Hands-on experience deploying, debugging, and managing application services across at least two major public cloud platforms, such as AWS, Azure, or GCP.
  • Experience building or integrating vector databases, embedding pipelines, semantic search, or retrieval-augmented generation (RAG) systems.
  • Practical experience developing LLM-powered applications or workflows using agent frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or equivalent technologies.
  • Strong Python skills for AI application development, combined with deep proficiency in a backend language such as Go, Java, or C++.
  • Strong relational database expertise, including complex SQL, schema design, indexing, transactions, and query optimization.
  • Experience with temporal data models, event-driven tracking, audit logging, or system-versioned tables.
  • Solid understanding of application security, including authentication, authorization, RBAC, row-level security, and multi-tenant isolation.
  • Familiarity with modern observability practices and tools, including structured logging and OpenTelemetry-based distributed tracing.
  • Experience designing and implementing production REST and/or gRPC APIs.
  • Experience with open-source projects in database, AI/ML application, or agent-tooling ecosystems is a plus.
  • Additional experience with MCP servers, A2A protocols, agent memory frameworks, graph databases, semantic caching, or Redis is advantageous.
  • Familiarity with packaging applications for on-premises or air-gapped environments, particularly regulated infrastructure, is beneficial.
  • Strong written communication, independent decision-making, collaboration skills, and an ownership-oriented mindset are essential for success in a small, distributed team.

  Benefits

  • Remote-first position available across India.
  • Highly autonomous environment with meaningful end-to-end ownership and direct technical impact.
  • Opportunity to work on cutting-edge AI application development, agent frameworks, database technologies, and enterprise data systems.
  • Exposure to multi-cloud and on-premises deployment environments.
  • Collaboration with experienced colleagues across international teams.
  • Strong opportunities for technical learning, professional growth, and hands-on experimentation.
  • Flexible, async-first working culture with an emphasis on written communication and focused execution.
  • Competitive compensation aligned with local market and compensation structures.
  • 25 days of paid annual leave plus applicable holidays.
  • Inclusive workplace that values diverse experiences, perspectives, and contributions.