AI Application Developer Location: India, Remote

Work Experience: 4-8 Years

Requirements:

- At least 1-2 years of experience with AI/ML, LLM, RAG, Databricks, or enterprise data platform solutions preferred.
- Solid programming experience in Python.
- Experience building backend APIs using FastAPI, Flask, Django, or similar frameworks.
- Hands-on experience with Azure Databricks, Apache Spark, Delta Lake, notebooks, jobs, and workflows.
- Understanding of Unity Catalog concepts such as catalogs, schemas, tables, volumes, permissions, access controls, and lineage.
- Experience with Mosaic AI, MLflow, model serving, LLM application deployment, or AI/ML platform services.
- Knowledge of RAG, Graph RAG, Document RAG, embeddings, semantic search, chunking strategies, and prompt engineering.
- Experience with vector databases or Databricks Vector Search.
- Understanding of knowledge graphs, triples, entities, relationships, graph query patterns, and entity-centric reasoning.
- Experience integrating with LLM provider APIs through secure platform services.
- Experience with event-driven or asynchronous processing patterns.
- Experience with REST APIs, WebSockets, message streams, and API gateway integration.
- Understanding deterministic rule processing, decision workflows, exception lifecycle management, or business process automation.
- Familiarity with EDI/X12 transaction processing is preferred.
- Good understanding of observability, logging, tracing, audit events, and error handling.
- Experience with Git, CI/CD pipelines, Agile delivery, and enterprise development practices.
- Experience with healthcare, pharma, supply chain, payer, provider, drug, pricing, claims, or regulated enterprise domains.
- Experience with EDI/X12 exception handling, upstream transaction processors, or healthcare data exchange.
- Experience with agentic AI applications, tool orchestration, MCP integrations,



or bounded tool execution.
- Knowledge of FDA drug data, DEA validation, NADAC/GPO pricing, EPCIS, VRS, or serialization workflows.
- Knowledge of PII redaction, prompt governance, responsible AI, human-in-the-loop approval, and auditability.
- Experience with Azure services such as Azure Key Vault, Azure Storage, Azure Event Hubs, Azure Functions, Azure DevOps, AKS, or Azure Monitor.
- Familiarity with Terraform or infrastructure-as-code.
- Exposure to Grafana, Prometheus, OpenTelemetry, or similar observability tools.

Qualifications: Bachelors or Masters degree in Computer Science, Information Technology, or a related field.

- Design and develop backend services for the AI-based Application.
- Implement operator-facing service flows supporting dashboards, exception workspaces, context inspection, and learning governance workflows.
- Develop transactional APIs for operator commands such as acknowledge, resolve, escalate, annotate, and case updates.
- Implement real-time event streaming for exception arrival, agent progress, queue updates, and re-evaluation events.
- Build and enhance EDI/X12 exception processing components including EDI Parser, exception normalization, and internal exception model mapping.
- Implement deterministic exception resolution flows including L1 reference-data lookups and L2 policy-based routing.
- Develop Agent Orchestrator workflows for L3 agentic resolution when deterministic rules cannot resolve exceptions.




- Integrate bounded resolution tools such as drug lookup, pricing check, serial verification, DEA check, and document lookup.
- Build integration with Graph RAG and Document RAG capabilities for contextual retrieval and decision support.
- Develop services such as Exception Service, Context Query Service, Learning Service, and Decision Trace Emitter.
- Implement decision trace capture for deterministic and agentic decisions to support auditability, explainability, and learning loops.
- Build ingestion and retrieval integrations using authoritative external sources such as drug registries, DEA registry, pricing data, serialization data, policies, documentation, and regulatory guidance.
- Implement feedback ingestion, pattern mining support, candidate rule synthesis support, routing optimization support, validation sandbox integration, and promotion workflows.
- Integrate application services with Azure Databricks, Unity Catalog, Mosaic AI, vector stores, graph stores, object stores, and model-serving services.
- Build REST, HTTPS, WebSocket, JSON-RPC, event-driven, and asynchronous interfaces as required.
- Implement secure access patterns using authentication, authorization, role-based access control, data governance, and audit controls.
- Ensure idempotent processing, metadata tracking, lineage, traceability, and consistency across persistence layers.
- Collaborate with QA, DevOps/MLOps, data engineering, architecture, security, and business teams.
- Participate in code reviews, design discussions, troubleshooting, performance tuning, and production readiness activities.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Application Developer (India)
🏢 NexTurn
📍 India