Awign
Website:
awign.com
Job details:
JOB DESCRIPTION – AI/ML Engineer (2-4 Years)
Job location – Bangalore/Coimbatore – Work from Office – 5days
Mumbai/Delhi – At client's place (Depends on client’s work mode)
What is the role about?
We are seeking a passionate and skilled Senior GenAI Engineer to join our GenAI organization and contribute to ShellKode’s next-generation AI initiatives.
This role focuses on building scalable GenAI and Agentic AI solutions using AWS cloud-native services, RAG architectures, and enterprise-grade orchestration workflows. The ideal candidate will have hands-on experience with LLM-based development, agentic frameworks, and AWS Bedrock.
What You Will Do
Design & Development
- Design and develop advanced GenAI solutions including:
- Retrieval-Augmented Generation (RAG)
- Agentic AI workflows (single-agent and multi-agent systems)
- Tool-calling and agent-to-agent orchestration
- Text-to-SQL, IDP (Intelligent Document Processing)
- Summarization, text generation, and multimodal use cases
- Build scalable GenAI services using:
- Amazon Bedrock (mandatory)
- LangChain, LangGraph, AgentCore
- Hugging Face APIs
- AWS cloud services (Lambda, API Gateway, S3, DynamoDB, Step Functions)
Engineering & Implementation
- Develop backend services and pipelines using Python (FastAPI/Flask).
- Implement embeddings, retrieval pipelines, chunking strategies, and grounding logic.
- Optimize RAG workflows, tool-calling patterns, and agentic reasoning.
- Deploy solutions using AWS-native tooling (SageMaker optional but not required for fine-tuning).
Execution & Collaboration
- Work closely with technical leads to execute assigned tasks and deliver project modules.
- Participate in requirement discussions, POCs, SOW execution, testing, and production rollout.
- Collaborate with cross-functional teams, including product owners, architects, and customer teams.
Quality, Performance & Innovation
- Monitor and improve solution robustness, latency, accuracy, and scalability.
- Implement guardrails, enterprise safety practices, and hallucination mitigation patterns.
- Stay updated on emerging LLM models, Bedrock capabilities, agent frameworks, and industry best practices.
Mandatory Experience
What you will need to have
- 2 to 4 years of overall engineering experience.
- Minimum 1 year of hands-on GenAI project experience.
- Mandatory Agentic AI experience, including:
- Multi-agent orchestration
- Tool-calling workflows
- Agent reasoning and state management
- Strong hands-on experience with AWS Cloud, including:
- Amazon Bedrock
- Lambda, API Gateway, S3, DynamoDB
- Step Functions / Event-driven architectures (preferred)
- Practical experience with:
- LangChain, LangGraph, AgentCore
- Vector databases (Pinecone, Weaviate, Chroma, Milvus)
Technical Skills
- Strong Python development experience.
- Knowledge of LLM APIs, embeddings, vector search, and RAG workflows.
- Experience building scalable backend systems and microservices.
- Familiarity with Docker, Git, CI/CD, and cloud-native deployment.
Soft Skills
- Strong analytical and problem-solving ability.
- Ability to work effectively with cross-functional teams.
- Good communication skills for customer and internal interactions.
Other Requirements
- Experience in a fast-paced startup or consulting environment is desirable.
- Prior customer-facing experience is an advantage.
- Candidates must be open to working from customer locations (onsite) when required.
- Willingness to travel occasionally for project needs
Click on Apply to know more.