Associate AI Engineer
Summary
Associate AI Engineer at Emplay builds LLM-powered features, RAG pipelines, and conversational AI applications using Python (FastAPI/Flask), LLM APIs (AWS Bedrock, OpenAI, Anthropic), and agent frameworks like LangChain, deployed on AWS services such as Lambda, S3, and DynamoDB. Remote role for candidates with 1–2 years of experience.
Compensation: ₹8L – ₹10L • No equity
Position: Associate AI Engineer
Experience: 1–2 years
Location - Remote / Work from Home
Salary (CTC) - 8 -10 LPA
No of Position - 5
Associate AI Engineer
We are looking for an AI Engineer with 1–2 years of hands-on experience in Generative AI, LLM applications, Python, and cloud technologies. You will work on building and improving AI-powered features, RAG-based applications, conversational systems, and integrations on AWS. The role involves working closely with senior engineers and product teams to develop, test, debug, and deploy reliable AI solutions while gaining exposure to production-scale AI systems.
Key Responsibilities
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Build and maintain LLM-powered features and conversational AI applications.
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Develop and improve RAG pipelines including document processing, embeddings, vector search, and retrieval.
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Work with LLM APIs such as AWS Bedrock, OpenAI, or Anthropic.
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Implement AI agents and tool-based workflows using frameworks such as LangChain or LlamaIndex.
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Develop backend services and APIs using Python (FastAPI / Flask).
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Integrate third-party platforms and services using REST APIs and webhooks.
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Work with AWS services such as Lambda, S3, DynamoDB, OpenSearch, SQS, and API Gateway.
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Write unit tests, integration tests, and automated regression tests for AI features.
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Monitor application logs, usage metrics, errors, and performance in development and production environments.
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Troubleshoot issues across AI, backend, API, and cloud components.
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Contribute to CI/CD pipelines and deployment processes.
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Follow security, authentication, access-control, and data-privacy practices.
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Collaborate with senior engineers and product teams to understand requirements and deliver features.
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Participate in code reviews and contribute to improving engineering practices.
Qualifications
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1–2 years of experience in software engineering, AI/ML engineering, or a related technical role.
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Good programming experience in Python and familiarity with FastAPI or Flask.
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Hands-on experience with LLM APIs such as AWS Bedrock, OpenAI, or Anthropic.
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Understanding of Generative AI concepts, prompt engineering, and conversational AI.
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Basic to intermediate understanding of RAG, embeddings, vector databases, and semantic search.
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Familiarity with AI/agent frameworks such as LangChain or LlamaIndex.
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Working knowledge of AWS services such as Lambda, S3, DynamoDB, OpenSearch, SQS, and API Gateway.
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Experience building and consuming REST APIs.
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Familiarity with Git and basic CI/CD concepts.
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Understanding of databases and data processing concepts.
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Good debugging and problem-solving skills.
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Ability to work in a collaborative engineering environment and learn new technologies quickly.
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Good communication skills and ability to explain technical issues clearly.
Preferred Skills
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Exposure to MCP (Model Context Protocol) and tool-based AI workflows.
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Experience with vector databases such as OpenSearch, Pinecone, or pgvector.
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Experience integrating enterprise platforms or SaaS APIs.
Skills
- Agentic AI
- AI
- Anthropic
- API
- API Gateway
- Authentication
- AWS
- AWS Bedrock
- CI/CD
- Cloud
- Conversational AI
- DynamoDB
- Embeddings
- FastAPI
- Flask
- Generative AI
- Git
- Lambda
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- MCP
- OpenAI
- OpenSearch
- pgvector
- Pinecone
- Prompt Engineering
- Python
- RAG
- REST
- S3
- SaaS
- Semantic Search
- SQS
- Vector Databases
- Vector Search
- Webhooks