AI Solutions Engineer

Role Overview

We are looking for a Forward Deployed Engineer / AI Solutions Engineer with strong experience across Cloud, Software Engineering, Data Engineering, and Generative AI. The ideal candidate should be comfortable owning AI applications end-to-end — from understanding business requirements and building solutions to cloud deployment, CI/CD, monitoring, and production support.

Responsibilities

• Design and deploy scalable AI applications on AWS/Azure.
• Build and maintain cloud infrastructure for production AI solutions.
• Develop containerized applications using Docker and implement CI/CD pipelines.
• Build robust backend APIs using Python, FastAPI, or Flask.
• Develop end-to-end AI applications with LLMs, RAG, and conversational agents.
• Build RAG pipelines involving chunking, embeddings, reranking, and hybrid search.
• Work with AWS S3, AWS OpenSearch, and cloud-based data pipelines.
• Implement document AI solutions involving PDFs, OCR, tables, images, and multimodal LLMs.
• Implement monitoring, logging, alerting, and observability for production applications.
• Follow software engineering best practices including Git, testing, code reviews, and release management.
• Work directly with business stakeholders and technical teams to understand requirements and deliver solutions.
• Participate in client-facing discussions, technical workshops, and production support.

Requirements

• 4–6 years of professional experience in Software / AI / Cloud Engineering.
• Strong hands-on experience with AWS or Azure.
• Strong Python programming skills.
• Experience with Docker, CI/CD, and Infrastructure as Code such as Terraform or CloudFormation.
• Experience with FastAPI / Flask and API development.
• Experience with AWS S3, AWS OpenSearch, and cloud data pipelines.
• Hands-on experience with LLMs, RAG, and Generative AI applications.
• Experience with LangChain / LlamaIndex / Hugging Face.
• Knowledge of vector databases such as Qdrant, Milvus, Pinecone, or Elasticsearch.
• Understanding of embeddings, chunking, reranking, and semantic search.
• Experience with Git, automated testing, and production deployment.
• Good understanding of monitoring/observability tools such as CloudWatch, Prometheus, Grafana, or ELK.
• Strong communication and client-facing skills.

Skills

• Python
• AWS
• Docker
• FastAPI
• Generative AI

Good to Have

• Kubernetes / EKS / AKS
• Terraform / CloudFormation
• Prometheus / Grafana / ELK / Datadog
• TypeScript / Front-end development
• PostgreSQL / MongoDB / Redis
• MCP or similar AI agent/tool frameworks
• Experience in Agentic AI / GenAI
• AWS/Azure cloud certification
• Pharmaceutical / Healthcare industry experience

Benefits

• Paid time off
• Provident Fund