Job Description
Educational Qualification* Bachelors Degree or higher in Information Systems, Computer Science, or equivalent experience.
Experience Range 5 - 7 Years
Tagline/Tech Stack Snapshot - AWS AL/ML
Role Summary - (To be filled by Practice /DO)
The AWS AI/ML Engineer is responsible for designing, developing, and deploying scalable machine learning and AI solutions leveraging AWS services. The role focuses on building data-driven applications, enabling advanced analytics, and implementing production-grade ML models that align with business objectives.
Primary (Must have skills)* - To be Screened by TA Team 2-3 years of experience in Generative AI, LLMs, and AI/ML integration (OpenAI, Anthropic, or similar).
4–5 years of experience with RESTful APIs, microservices architecture, AWS cloud platform services (lambda, dynomoDB, S3, API gateway etc).
2-3 years of experience in AWS Bedrock eco system, AWS Q, textract, AWS Sagemaker .
2-3 years of experience in prompt engineering, RAG workflows, NLP, semantic search, and intent recognition.
2-3 years of experience with AI orchestration frameworks like LangChain, Semantic Kernel, or AutoGen.
4–5 years of experience with modern development frameworks and Python libraries.
Strong understanding of SQL, NoSQL, and vector databases.
Experience with Git, CI/CD pipelines, and DevOps practices.
Why This Role Matters - New addition (To be filled by Practice /DO) This is one of the most inportant engagements for our customer. What You'll Do/
Job Description of Role* (RNR) - To be Evaluated by Technical Panel (Define it to give more clarity) Design and develop end-to-end AI/ML solutions using AWS services such as SageMaker, Bedrock, Lambda, and S3
Build, train, evaluate, and deploy machine learning models for real-world use cases
Develop data pipelines for ingestion, transformation, and feature engineering
Integrate AI/ML models into applications and enterprise systems through APIs and microservices
Work on Generative AI use cases (e.g., LLMs, chatbots, copilots) using AWS AI services
Optimize model performance, scalability, and cost efficiency in cloud environments
Collaborate with data engineers, architects, and business stakeholders to translate requirements into technical solutions
Ensure compliance with security, governance, and best practices for AI/ML systems
Monitor model performance and implement continuous improvement pipelines Soft skills/other skills - To be Evaluated by Hiring Manager (To define how this will be evaluated) Communication Skills:
Communicate effectively with internal and customer stakeholders (technical and non-technical )
Communication approach: verbal, emails and instant messages
Interpersonal Skills:
Strong interpersonal skills to build and maintain productive relationships with team members
Provide constructive feedback during reviews and be open to receiving the feedback.
Problem-Solving and Analytical Thinking:
Capability to troubleshoot and resolve issues efficiently.
Analytical mindset
Task/ Work Updates
Prior experience in working on Agile/Scrum projects with exposure to tools like Jira/Azure DevOps
Provides regular updates, proactive and due diligent to carry out responsibilities What Success Looks Like (6–12 Months) -
Expected Outcome Successfully delivers scalable and production-ready AI/ML solutions on AWS
Demonstrates strong ownership in translating business problems into effective ML models
Achieves high model accuracy and performance aligned with defined KPIs
Builds efficient, cost-optimized, and maintainable cloud-based ML pipelines
Enables faster decision-making and measurable business impact through AI solutions
Proactively identifies opportunities to leverage AI/ML or GenAI for innovation
Ensures seamless integration of models into enterprise workflows and applications
Maintains high standards of documentation, security, and compliance
Gains stakeholder confidence through consistent delivery, communication, and technical expertise Secondary Skills (Good to have) Data Engineering Basics
Collaboration & Agile Why Join Us - New Addition
WinWire's platform: Microsoft Partner of the Year (2025), Great Place to Work certified, 19+ years of enterprise delivery excellence
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