About the Role
We are looking for a highly skilled AI / ML Engineer with strong hands-on experience in Generative AI, AWS Bedrock, LLM Agents, and Python-based AI development. The role involves designing, building, and deploying production-grade GenAI solutions while collaborating closely with cross-functional and client-facing teams.
This position is ideal for professionals who enjoy working on real-world AI use cases, building scalable AI systems, and translating business needs into intelligent, cloud-native solutions.
Requirements
Experience: 8+ Years (4+ Years in AI/ML)
Location: Hyderabad
Work Mode: Work From Office
Shift: General Shift
Employment Type: Full-Time (Permanent)
Notice Period: Immediate Joiners Preferred
Required Skills & Experience
8+ years of overall experience with 4+ years in AI/ML development.
Strong hands-on experience with AWS Bedrock, Generative AI models, and LLM Agents.
Proficiency in Python (NumPy, Pandas, scikit-learn, LangChain, etc.).
Experience building AI microservices, APIs, and cloud-based applications.
Strong understanding of ML algorithms, NLP, embeddings, vector stores, and AI evaluation.
Experience working in a service-based delivery model supporting multiple client projects.
Strong communication, analytical, and problem-solving skills.
AI / ML & Generative AI Development
Design, build, and deploy GenAI applications and LLM-powered agents using AWS Bedrock.
Develop prompt-engineered workflows, RAG pipelines, embeddings, and agentic automation solutions.
Build and optimize scalable ML models using Python for production readiness.
AWS Cloud & AI Platform Integration
Work extensively with AWS services such as Bedrock, Lambda, S3, Glue, API Gateway, and DynamoDB for AI workflows.
Integrate LLMs into existing applications using APIs, SDKs, and cloud-native architectures.
Optimize model performance, latency, cost, reliability, and scalability on AWS.
Solution Engineering & Delivery
Understand client requirements and translate them into robust AI/ML solution designs.
Build POCs, prototypes, and production-grade AI solutions across multiple client engagements.
Support post-deployment activities including fine-tuning, enhancements, and version upgrades.
Collaboration & Stakeholder Management
Work closely with data engineers, product teams, and delivery managers to build cohesive AI-driven systems.
Participate in requirement discussions, solution reviews, and architectural decision-making.
Clearly communicate AI insights, model behavior, and recommendations to both technical and non-technical stakeholders.
Quality, Documentation & Governance
Maintain clean, well-documented code and follow model governance best practices.
Ensure compliance with data privacy, security, and responsible AI guidelines.
Monitor model performance and continuously improve AI pipelines and workflows.
About the Company
Our client is a global digital engineering and technology services organization delivering advanced cloud, data, and AI-driven solutions to enterprise customers. With a strong focus on innovation, scalability, and business impact, the organization works on cutting-edge AI, automation, and modern cloud transformation initiatives across multiple industries in a service-based delivery environment.