AI Integration Engineer

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.