Empower Solutions
Website:
empower-solutions.com
Job details:
Empower Solutions is looking for an AI Engineer / GenAI Engineer with strong hands-on 3+ years of experience in Agentic AI, LLM-based applications, Python, AWS AI/ML services, and data engineering. The candidate should be capable of designing, developing, integrating, and deploying AI-powered solutions in a production environment.
Key Responsibilities
- Design and develop Agentic AI solutions, AI agents, multi-step workflows, and tool/function calling.
- Build LLM-based applications using OpenAI, Anthropic, AWS Bedrock, or similar platforms.
- Develop RAG, knowledge-based AI solutions, prompt engineering, embeddings, and vector search.
- Work extensively with AWS AI/ML services, particularly:
- AWS Bedrock
- Amazon Textract / OCR
- Amazon SageMaker
- Amazon Comprehend and other relevant AI services
- Develop AI/ML backend services and integrations using Python and frameworks such as FastAPI/Flask.
- Design and maintain ETL/data pipelines for AI and business applications.
- Work with databases including DynamoDB, PostgreSQL, and other relational/NoSQL databases.
- Integrate structured and unstructured data into AI pipelines and knowledge systems.
- Build and maintain REST APIs and microservices supporting AI solutions.
- Implement CI/CD pipelines using Git/Bitbucket, Docker, and cloud deployment practices.
- Work with AWS services such as Lambda, S3, SQS, SNS, ECS/EKS, API Gateway, CloudWatch, and other supporting services.
- Implement monitoring, logging, security, scalability, and performance optimization for AI applications.
- Collaborate with engineering and business teams to convert use cases into scalable AI solutions.
Required Skills
- Strong hands-on Python development experience.
- Practical experience with Generative AI and LLMs.
- Strong understanding and hands-on experience with Agentic AI / AI Agent development.
- Experience with AWS Bedrock and other AWS AI/ML services.
- Experience with OCR / document processing, preferably Amazon Textract.
- Experience building RAG and LLM-powered applications.
- Good knowledge of DynamoDB and PostgreSQL.
- Experience with ETL/data pipelines and data processing.
- Experience with Git/Bitbucket and CI/CD pipelines.
- Good understanding of REST APIs, microservices, Docker, and cloud-based application deployment.
- Strong problem-solving and software engineering skills.
Good to Have
- Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or similar frameworks.
- Experience with vector databases such as pgvector, Pinecone, OpenSearch, Qdrant, or similar.
- Experience with AWS Lambda, S3, SQS, Step Functions, ECS/EKS, API Gateway, and CloudWatch.
- Exposure to Machine Learning / ML model integration.
- Experience with AI evaluation, observability, security, and cost optimization.
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