AI/ML Solution Engineer

Location: Gurgaon
Work Model: Hybrid – 3 days from office
Shift: Second Shift – 2:30 PM to 10:30 PM
Experience: 3–5 Years Only

Role Overview

We are looking for an experienced AI/ML Solution Engineer with 3–5 years of hands-on experience in AI/ML, Generative AI, AWS, Python, LLMs, RAG, and AI agent-based solutions.

The ideal candidate should have strong practical experience in building and delivering AI/GenAI solutions, with a positive understanding of Machine Learning concepts, model evaluation, AI Evals, observability, and responsible AI.

Python is mandatory. Familiarity with Java is preferred.

Key Responsibilities

- Design, develop, deploy, and maintain cloud-native applications and services on AWS.
- Build and integrate Generative AI solutions using Amazon Bedrock, Amazon SageMaker, and Bedrock AgentCore.
- Develop AI agents and multi-agent workflows using Bedrock Agents, AgentCore, AWS Strands SDK, LangChain, LangGraph, or similar frameworks.
- Build AI-powered applications using LLMs, RAG architectures, and agent-based solutions.
- Develop scalable and resilient event-driven solutions using EventBridge, SQS, SNS, Lambda, and Step Functions.
- Design and develop REST APIs, microservices, and serverless applications following AWS best practices.
- Implement data storage and retrieval solutions using RDS, Aurora, DynamoDB, and S3.
- Partner with architects and engineering teams to translate business requirements into technical solutions.
- Contribute to system design, architecture reviews, and technical discussions.
- Troubleshoot production issues and optimize application performance, reliability, scalability, and cost.
- Develop infrastructure automation and CI/CD pipelines using Infrastructure as Code principles.
- Implement AI observability to monitor model performance, prompt effectiveness, response quality, latency, usage patterns, and application health.
- Develop and execute AI Evaluation (AI Evals) frameworks to assess:
- Model accuracy
- Relevance
- Groundedness




- Safety
- Response quality
- Overall GenAI/agent effectiveness
- Establish monitoring, logging, tracing, and evaluation mechanisms to identify hallucinations, drift, performance issues, and reliability concerns.
- Implement AI guardrails, content safety controls, auditability, and risk management processes.
- Follow enterprise AI governance, data privacy, security, compliance, and responsible AI practices.

Mandatory Skills

- 3–5 years of relevant experience in AI/ML / GenAI solution engineering
- Strong hands-on Python development – Mandatory
- Hands-on experience delivering AI/Generative AI solutions
- Strong understanding of Machine Learning concepts
- Practical knowledge of AI Model Evaluation / AI Evals – Mandatory
- Experience with LLMs, RAG, prompt engineering, and AI agents
- Hands-on experience with AWS AI/ML services, preferably Bedrock and SageMaker
- Experience with Bedrock AgentCore / AI agent frameworks
- Knowledge of LangChain, LangGraph, AWS Strands SDK, or similar frameworks
- Understanding of cloud-native architecture and distributed systems
- Experience with REST APIs, microservices, and serverless architecture
- Understanding of event-driven architecture
- Strong system design and problem-solving skills

Preferred Skills

- Familiarity with Java
- AWS services such as Lambda, S3, SQS, SNS, EventBridge, Step Functions, DynamoDB, RDS, and Aurora
- CI/CD and Infrastructure as Code
- AI observability and monitoring
- AI guardrails and responsible AI
- Experience with production-grade GenAI applications

AI Rating Requirement

Pay: ₹500,719.15 - ₹1,802,472.51 per year

Benefits:

- Provident Fund

Application Question(s):

- How many years of hands-on experience do you have in AI/ML and Generative AI?
- How many years of hands-on Python development experience do you have?
- Which AWS AI/ML services have you worked hands-on with?
- Do you have hands-on experience building LLM-based applications using RAG?
- Are you comfortable working in the 2:30 PM – 10:30 PM shift?

Work Location: Hybrid remote in Gurugram, Delhi

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