Agentic & Generative AI developer

About Sutherland

Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise.

We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence.

We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships.

Sutherland

Unlocking digital performance. Delivering measurable results.

We are looking for a skilled and delivery-focused Technical Developer to design, build, and deploy innovative AI applications leveraging Agentic AI frameworks and GenAI technologies. The candidate will be responsible for transforming architecture into scalable solutions, optimizing AI workflows, and driving production-grade implementations.

• Key Responsibilities: - Develop, test, and maintain Agentic AI workflows using Langchain, LangGraph, Google ADK, etc.

• Convert AI architecture into working prototypes and deployable components.
• Build and enhance RAG pipelines, agent-based applications, and knowledge retrieval systems.
• Perform data preprocessing, feature engineering, and model optimization.
• Collaborate with teams to build reusable GenAI modules and enforce coding best practices.
• Manage cloud-based deployments on AWS, Azure, or GCP.
• Debug and resolve system bottlenecks, ensuring performance and reliability.
• Keep up with advancements in GenAI, LLMs, and autonomous agents.

• Required Skills & Qualifications: - Strong coding background in Python with AI/ML engineering experience.

• Proven track record of working with LLMs, Transformer models, and Agentic AI frameworks.
• Familiarity with prompt engineering, API integration, and model orchestration.
• Hands-on experience with RAG architectures, vector databases, and agent-to-agent communication (MCP).
• Working knowledge of SQL/NoSQL, data warehousing, and analytical querying.
• Understanding of CI/CD pipelines, Docker, and Kubernetes for model lifecycle management.

• Preferred Qualifications (Good to Have): - Experience with LangGraph agent orchestration or similar agentic toolkits.

• Exposure to enterprise-grade AI applications in finance, healthcare, or e-commerce.

• Experience Level: - 3–7 years of relevant experience in AI/ML or full-stack AI solution development.
• Education:

• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field.

All your information will be kept confidential according to EEO guidelines.

- Develop, test, and maintain Agentic AI workflows using Langchain, LangGraph, Google ADK, etc.

• Convert AI architecture into working prototypes and deployable components.
• Build and enhance RAG pipelines, agent-based applications, and knowledge retrieval systems.
• Perform data preprocessing, feature engineering, and model optimization.
• Collaborate with teams to build reusable GenAI modules and enforce coding best practices.
• Manage cloud-based deployments on AWS, Azure, or GCP.
• Debug and resolve system bottlenecks, ensuring performance and reliability.
• Keep up with advancements in GenAI, LLMs, and autonomous agents

• Required Skills & Qualifications: ### - Strong coding background in Python with AI/ML engineering experience.

• Proven track record of working with LLMs, Transformer models, and Agentic AI frameworks.
• Familiarity with prompt engineering, API integration, and model orchestration.
• Hands-on experience with RAG architectures, vector databases, and agent-to-agent communication (MCP).
• Working knowledge of SQL/NoSQL, data warehousing, and analytical querying.
• Understanding of CI/CD pipelines, Docker, and Kubernetes for model lifecycle management.

Preferred Qualifications (Good to Have):

- Experience with LangGraph agent orchestration or similar agentic toolkits.

• Exposure to enterprise-grade AI applications in finance, healthcare, or e-commerce

• Experience Level: ### - 3–7 years of relevant experience in AI/ML or full-stack AI solution development.

Education:**

• Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field.

All your information will be kept confidential according to EEO guidelines.