Senior/Lead Data Scientist – AIML Engineer, AI Automation Engineer

Naveera Technology LLC

. Lead the architecture and development of AI-driven automation platforms and intelligent workflows .

Posted 9/21/2026full-timeIndiaSenior💰 $20,000 - $35,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Python backend engineering, AI-driven automation, and scalable architecture design. Proficient in developing and integrating AI solutions within healthcare workflows and enterprise systems while ensuring security and best practices in software development.

Highest-signal resume keywords

Expert Python Backend EngineeringAI Agent FrameworksMicroservices ArchitectureTemporal Workflow OrchestrationOAuth2, JWT, SSO, RBAC/ABAC

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonFastAPIFlaskDjangoREST APIsAsynchronous ProgrammingC#/.NET IntegrationEvent-Driven ArchitectureSQL ServerPostgreSQL

Soft Skills

MentoringCollaborationCode Review

Tools & Technologies

AWSAzureDockerGitCI/CDKubernetesKafkaRabbitMQTerraformMLflow

Industry Keywords

Healthcare Domain KnowledgeAI Automation PlatformsRCMClaimsPayer/Provider Workflows

Tech Stack

Tools & technologies

Amazon RedshiftAWSAzureDistributed SystemsDjangoDockerFlaskGraphQLKafkaKubernetesMicroservicesNoSQLPostgresPythonRabbitMQReactRedisSQLTerraform.NET

About the role

Key responsibilities & impact

Lead the architecture and development of AI-driven automation platforms and intelligent workflows
Build scalable Python backend services, REST APIs, asynchronous processing, and microservices
Design workflow orchestration using Temporal or equivalent workflow engines for long-running business processes
Develop AI agents using modern LLM frameworks and AWS AI services
Integrate Python services with C#/.NET applications, enterprise systems, and external APIs
Design secure, scalable, stateful/stateless backend architectures with event-driven patterns
Implement authentication and authorization using OAuth2, JWT, SSO, RBAC/ABAC
Develop AI-powered healthcare workflows across RCM, enrollment, claims, payer/provider integrations, and document automation
Build full-stack AI applications spanning backend APIs, workflow services, AI orchestration, and frontend integration
Implement AI Ops practices including monitoring, observability, model lifecycle management, logging, evaluation, and production support
Drive engineering best practices, code quality, CI/CD, and documentation
Mentor development teams and collaborate with cross-functional teams

Requirements

What you’ll need

7 to 15 years of experience
Expert Python backend engineering
Experience with FastAPI, Flask or Django
REST APIs, WebSockets, and asynchronous programming
Microservices architecture
External API integrations
C#/.NET integration experience
Temporal or equivalent workflow orchestration
Event-driven architecture
Distributed processing and long-running workflow management
State management
AI agent frameworks such as CrewAI, AutoGen, Semantic Kernel, or LangGraph
LLM integration with Amazon Bedrock, OpenAI, or Azure OpenAI
Prompt engineering and guardrails
RAG architecture
Vector databases such as ChromaDB, Pinecone, or pgvector
MCP (Model Context Protocol) and AI skills/tooling knowledge
OAuth2, JWT, SSO, RBAC/ABAC, API security, and secrets management
AWS or Azure
Docker, Git, and CI/CD pipelines
Monitoring, logging, AI Ops, model monitoring, observability, production deployment, and support
SQL Server, PostgreSQL, Redshift, Redis, NoSQL databases, and vector databases
Experience building enterprise AI automation platforms
Healthcare domain knowledge involving RCM, claims, eligibility, enrollment, prior authorization, or provider/payer workflows
Understanding of distributed systems and scalable backend architecture
Experience integrating AI solutions into existing enterprise applications
Experience leading technical teams, conducting code reviews, and mentoring engineers
Experience delivering production-grade full-stack AI applications
Kubernetes, Kafka/RabbitMQ, GraphQL, Playwright/browser automation, Terraform/infrastructure as code, Snowflake, Databricks, MLflow/model lifecycle management, React or modern frontend frameworks, and FHIR/HL7 are nice to have

Benefits

Comp & perks

Flexible Remote/Hybrid work environment
Exposure to global enterprise customers
Collaborative, innovation-driven engineering culture
Continuous learning and certification opportunities