Solution Engineer

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

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 good 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, and 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

- Hands-on experience delivering AI/Generative AI solutions

- Strong understanding of Machine Learning concepts

- Practical knowledge of AI Model Evaluation / AI Evals

- 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

Skills

Python, AWS, Machine Learning, LangChain, LangGraph, Generative AI, Java, AWS SageMaker, LLM, Artificial Intelligence