Data Scientist

Company: Numeric Technologies

Company Website: https://numerictech.com

Type: Permanent with Numeric Technologies

Numeric, incorporated in 1996 is a worldwide Business & Information Technology, Consultingand Services company. Headquartered in Chicago, IL with additional offices in Miami, Silicon Valley, Luxembourg, UK as well as delivery centers in India (Bengaluru,Hyderabad,Chennai) to serve our customers on offshore needs.We at Numeric Technologies pride ourselves for providing our customers with the best services and solutions. We believe that the right people in the right time and the right position are the key to our companys improvement; we continue to endeavor and develop our company through our corporate culture and values.

Position: AI/ML Engineer

Experience: 6+ Years

Location: BLR

Shift: 3 PM to 11 PM

Notice Period : 0 to 15 day

Job Summary:

We are seeking a hands-on Senior AI Engineer (57 years experience) to design and build enterprise-grade Agentic AI applications within the AWS ecosystem.

The ideal candidate has strong Python development experience, practical exposure to Large Language Models (LLMs), and hands-on experience building Retrieval-Augmented Generation (RAG) and multi-agent workflows using frameworks such as LangChain/LangGraph or similar.

This role focuses on designing, integrating, deploying, and operating AI-powered services on AWS, ensuring scalability, security, reliability, and cost efficiency.

Key Responsibilities:

Design and implement Agentic AI workflows using LLMs (OpenAI, Bedrock, or equivalent).

Develop Python-based backend services for: Model orchestration, Tool/function calling, Context management, API exposure.

Build Retrieval-Augmented Generation (RAG) pipelines using vector databases (e.g., Pinecone, FAISS, OpenSearch).

Design secure and scalable AI APIs using AWS services such as Lambda and API Gateway.

Deploy and manage AI workloads using AWS Bedrock and SageMaker.

Implement CI/CD pipelines and Infrastructure as Code (CloudFormation/CDK/Serverless Framework).

Apply MLOps best practices including: Model versioning, Prompt versioning, Monitoring and observability, Logging and performance tracking.

Ensure AI systems are: Reliable and resilient, Secure (IAM, policies, encryption), Cost-aware and optimized.

Collaborate with product owners, enterprise application teams, and data engineers to integrate AI solutions into business workflows.

Contribute to AI use case evaluation and architecture design discussions.

Required Skills & Experience:

57 years of software engineering experience with strong Python expertise.

Hands-on experience integrating LLM platforms such as OpenAI or AWS Bedrock.

Practical experience building: RAG systems, Multi-agent or agentic workflows, Tool-calling or function-calling architectures.

Experience with frameworks such as:

o LangChain / LangGraph (or equivalent orchestration frameworks).

Solid experience with AWS services: Bedrock, SageMaker (model hosting/inference; full training expertise not mandatory), Lambda, ECS, S3, API Gateway, IAM etc.

Experience deploying applications using Infrastructure as Code (CloudFormation, CDK, Serverless Framework).

Understanding of: Prompt engineering, LLM limitations and guardrails, Context window management, Token optimization.

Familiarity with vector databases and embedding workflows.

Strong debugging, problem-solving, and system design skills.

Preferred Qualifications:

Experience designing secure enterprise AI solutions.

Exposure to SAP AI, enterprise ERP integration, or business process automation.

Experience implementing observability for AI systems (latency, hallucination tracking, usage monitoring).

Experience with TypeScript for AI tooling or frontend integrations.