Positions : AI Integration Engineer

Experience: 3-5 Years  
Location: Pune

mail us your profile at hr@decentjob.in 

Role summary

• Build the data infrastructure and integration layer powering AI-driven automation and business intelligence initiatives.
• Work at the intersection of data engineering, API development, and AI, enabling multi-agent workflows where AI agents and humans collaborate via bidirectional delegation.

Key Responsibilities

• API development and data exchange
  • Design, develop, and maintain scalable RESTful APIs for data exchange between systems
  • Build real-time data pipelines and streaming architectures to support AI agent operations
  • Implement API gateways, rate limiting, authentication, and security best practices
  • Create API documentation and integration guides; monitor and optimize performance and availability
• AI agent integration and automation
  • Integrate and orchestrate AI agents (LLMs, ML models, autonomous agents) into workflows
  • Design agent-to-agent communication protocols and data handoffs
  • Build middleware/connectors so agents can safely access enterprise data sources
  • Implement feedback loops and monitoring for agent performance
  • Create workflows combining multiple AI capabilities (RAG, function calling, multi-agent systems)
• Data infrastructure and BI enablement
  • Maintain and optimize data warehouses, data lakes, and vector databases
  • Build ETL/ELT pipelines that prepare data for AI consumption
  • Implement data quality, validation, and governance frameworks
  • Design data models that support analytical queries and AI agent operations
  • Expose data through APIs for dashboards/reporting; enable self-service data access via documented APIs and MCP servers

Qualifications (level-flexible)

• Core requirements
  • Strong Python and SQL
  • Solid grounding in data engineering concepts (pipelines, modeling, quality, orchestration)
  • Familiarity with relational and NoSQL databases (examples: PostgreSQL, MongoDB, Redis)
  • Exposure to cloud platforms (AWS, GCP, or Azure)
  • Working knowledge of API patterns and integration technologies (REST; plus exposure to GraphQL/gRPC/WebSockets/message queues is a plus)
• AI/agentic familiarity (preferred, not mandatory for interns/new grads)
  • Understanding of LLM APIs, prompt engineering, RAG systems, vector databases
  • Exposure to agent frameworks (examples: LangChain, LlamaIndex, Pydantic AI, AutoGen, CrewAI)
• Additional pluses
  • Docker/Kubernetes, Terraform, CI/CD
  • Event-driven architectures and microservices
  • Data security/compliance basics (e.g., encryption, access controls; familiarity with GDPR/HIPAA/PHI is a plus)

What you’ll work with (typical stack)

• Python, SQL, JavaScript/TypeScript, YAML
• Airflow, dbt, Spark, Polars, pyArrow
• FastAPI, GraphQL, Kafka, Redis
• OpenAI/Anthropic APIs, vector databases, MCP protocol
• AWS (Lambda, S3, RDS, Bedrock, SageMaker) or equivalents

Hiring note

• We are open to strong interns and fresh graduates who demonstrate capability via projects, internships, or open-source contributions.