Application Developer

Eviden, part of the Atos Group, with an annual revenue of circa € 5 billion is a global leader in data-driven, trusted and sustainable digital transformation. As a next generation digital business with worldwide leading positions in digital, cloud, data, advanced computing and security, it brings deep expertise for all industries in more than 47 countries. By uniting unique high-end technologies across the full digital continuum with 47,000 world-class talents, Eviden expands the possibilities of data and technology, now and for generations to come.

Senior Tech Lead – AWS AI (Anthropic) Experience: -

Minimum 12–15 years of total IT experience, with at least 5–7 years in AI/ML engineering and solution implementation. Strong hands-on expertise in building and deploying GenAI solutions on AWS using services like Amazon Bedrock, SageMaker, and integration with Anthropic Claude models. Location: Bangalore / Pune (hybrid/flexible on a case-by-case basis) 

Role Overview: -

The Senior Tech Lead – AWS AI (Anthropic) will be responsible for driving the development and deployment of AI/ML solutions using AWS-native services, particularly leveraging Amazon Bedrock and Claude by Anthropic. The role demands a hands-on technical leader who can guide engineering teams, collaborate with architects, and translate solution blueprints into high-quality implementations. The ideal candidate is expected to bring strong experience in delivering GenAI solutions, coding expertise in Python, and a deep understanding of AWS AI/ML services. 

Key Responsibilities:-

• Lead technical implementation of AI solutions using AWS Bedrock (Claude, Titan), Amazon SageMaker, Lambda, and other AWS-native services.
• Translate high-level solution designs into detailed technical tasks and oversee delivery across engineering teams.
• Develop and optimize prompts, fine-tune models, implement RAG patterns, and integrate vector search solutions (e.g., OpenSearch, Pinecone).
• Build scalable and secure APIs to expose GenAI capabilities to enterprise applications.
• Design and implement end-to-end ML pipelines using SageMaker, Step Functions, and MLOps best practices.
• Ensure compliance with AWS security best practices including IAM roles, data encryption, and responsible AI principles.
• Collaborate closely with solution architects, product owners, and DevOps teams for successful deployment and monitoring.
• Support PoCs and pilots, ensuring timely delivery, performance benchmarks, and smooth handover to production.
• Mentor junior engineers, promote clean coding practices, and contribute to reusable code assets and internal GenAI accelerators. 

Required Skills and Competencies: -

• Strong hands-on experience with Amazon Bedrock and Claude models (prompt tuning, RAG, embeddings).
• Proficiency in Python and cloud-native development using RESTful APIs, AWS SDKs, and event-driven patterns.
• Deep knowledge of Amazon SageMaker (model training, deployment, tuning, pipelines).
• Experience implementing vector search, embedding pipelines, and prompt engineering strategies.
• Familiarity with LangChain, Haystack, or equivalent GenAI orchestration frameworks.
• Knowledge of AWS services including Lambda, API Gateway, Step Functions, DynamoDB, and IAM.
• Exposure to model evaluation, cost-performance optimization, and real-time inference patterns.
 

Desirable Qualifications: -
• AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect – Associate/Professional.
• Experience with CI/CD pipelines, model versioning, and infrastructure-as-code using CDK or Terraform.
• Knowledge of GenAI applications such as chatbots, summarization tools, code assistants, and content generation.
• Exposure to third-party models (e.g., Cohere, Stability AI) integrated via AWS Marketplace. 

Soft Skills: -
• Strong problem-solving and debugging skills with a bias for action.
• Excellent verbal and written communication; able to explain complex technical concepts clearly.
• Leadership mindset with the ability to coordinate across distributed teams.
• Adaptability and enthusiasm for learning new GenAI tools and technologies in a fast-paced environment.

Let’s grow together.