Data Engineer (Pharma domain Must)

Role: AI Solutions Engineer with Pharma Domain

Location: India (Remote )

Must have Pharma Domain exp ( No Healthcare and Lifesciences)

Key Responsibilities

Infrastructure and Cloud Engineering

• Cloud Architecture: Design, implement, and manage scalable and secure infrastructure on cloud platforms (AWS/Azure) for production AI applications

• Containerization and Orchestration: Develop and maintain containerized environments (Docker) for model and application deployment

• CI/CD Pipelines: Build and optimize continuous integration and delivery pipelines for automated testing, builds, and deployments

Software Engineering and Productionization

• Full Stack Development: Build robust APIs (FastAPI, Flask) and user interfaces for AI applications, ensuring end-to-end integration

• Quality and Testing: Implement comprehensive testing strategies (unit, integration, E2E) and code reviews to ensure code quality

• Version Control and Code Management: Establish Git flow practices, branching strategies, and release management

• Technical Documentation: Create and maintain architecture documentation, runbooks, deployment guides, and operational procedures

Monitoring, Observability, and Performance

• Observability: Implement logging, tracing, and metrics solutions (Prometheus, Grafana, ELK Stack, CloudWatch, Application Insights)

• Performance and Optimization: Monitor and optimize latency, throughput, resource utilization, and operational costs

• Alerting and Incident Response: Configure proactive alerting systems and establish incident response procedures

AI Applications and RAG

• Conversational Agents: Implement LLM agents with function calling, state management, guardrails, and safety mechanisms

• RAG Pipelines: Build indexing, chunking, embeddings, reranking, and hybrid retrieval pipelines for high-precision answers

• Document AI: Process and parse complex PDFs using OCR, multimodal LLM image understanding, table extraction, and layout-aware parsing

• Prompt Engineering: Design and iterate prompts, templates, and few-shot examples; run A/B and automated evaluations

Project Management and Communication

• Project Documentation: Create and maintain written project documentation including requirements, technical designs, test plans, runbooks, release notes, user guides, risk/issue logs, and change records

• Stakeholder Communication: Produce status updates, meeting notes, incident/outage notices, and decision summaries

• Workshops and Discussions: Lead customer/client-facing workshops and discussions

Skills

Essential

Cloud and Infrastructure

• 3+ years of experience designing and implementing cloud infrastructure (AWS/Azure) for production applications

• Practical expertise in containerization (Docker)

• Knowledge of Infrastructure as Code (Terraform, CloudFormation, or similar)

• Solid experience with CI/CD (GitHub Actions, GitLab CI, Jenkins, Azure DevOps) and deployment automation

• Experience with cloud networking, security, IAM, and secrets management (Vault, AWS Secrets Manager, Azure Key Vault)

• Hands-on experience building data pipelines on cloud and working with cloud data sources and services (S3, AWS OpenSearch, data lakes); not a dedicated data engineer role, but comfort with data-centric cloud services is required

Software Engineering

• 3+ years of experience in full stack development with strong Python programming skills

• Solid software engineering practices: design patterns, SOLID principles, clean code, code reviews

• Experience with automated testing (pytest, unittest, integration tests, E2E tests)

• Proficiency in Git, branching strategies, and release management

• Working proficiency in TypeScript for front-end/UI development, sufficient to build and connect user interfaces alongside Python back-end services

• Knowledge of relational and NoSQL databases (PostgreSQL, MongoDB, Redis, or similar)

AI and Machine Learning

• Experience with LLM frameworks (LangChain, LlamaIndex) and Hugging Face

• Practical knowledge of vector databases (Qdrant, Milvus, Pinecone, ElasticSearch)

• Experience with chunking strategies, embedding selection/tuning, and rerankers

• Familiarity with complex document processing: table extraction, layout parsing, OCR, and multimodal LLM-based image description

Soft Skills and Business Engagement

• 3+ years of experience leading customer/client-facing workshops and discussions

• Demonstrated business analysis skills and ability to translate requirements into technical solutions

• Excellent technical communication and documentation skills

Desirable

• Experience with container orchestration (Kubernetes, EKS, AKS)

• Hands-on experience with observability tools (Prometheus, Grafana, ELK Stack, Datadog, New Relic)

• Cloud certifications (AWS Solutions Architect, Azure Solutions Architect, GCP Professional Cloud Architect)

• Familiarity with security best practices and compliance

• Sound understanding of emerging developments in AI, including generative AI and agentic AI

• Experience in the pharmaceutical industry