Senior Agentic AI Engineer (Python)

Job description

ABOUT THE ROLE

In this role, you will design and build next-generation agentic AI systems — including LLM-powered code generation pipelines, multi-agent workflows, and RAG applications — within SoftServe's AI and Data Science Center of Excellence, a team of 170+ experts including Data Scientists, ML Engineers, and Architects. Your work will directly shape how clients leverage autonomous AI at production scale, from requirements gathering through to deployment.

RESPONSIBILITIES

- Design and develop agentic pipelines for code generation, using LLMs and agent frameworks to produce functional, high-quality code artifacts aligned with business and technical requirements

- Build and maintain LLMOps pipelines using tools such as MLflow, Langfuse, or LangSmith to ensure model observability, reproducibility, and prompt versioning across production workflows

- Collaborate closely with clients and stakeholders to understand use cases, gather requirements, and translate them into scalable, production-ready agentic ML solutions

- Design and implement MCP (Model Context Protocol) integrations to connect LLMs with external tools, APIs, and data sources, extending the capabilities of agentic systems in a standardised, interoperable way

- Develop and deploy applications for NLP, RAG systems, and multimodal models (text and image), integrating them into end-to-end ML service architectures

- Act as human-in-the-loop to validate agentic outputs against quality, compliance, and contextual standards

- Support the productionization of large language models and advanced AI systems, including CI/CD/CT pipeline setup and cloud deployment on AWS, Azure, or GCP

- Contribute to the team's knowledge base by capturing reusable prompt patterns, templates, and playbooks that accelerate discovery and delivery

REQUIREMENTS

- Minimum 3 years of experience building and deploying production-grade applications using the Python ecosystem

- Strong Python proficiency for automation and data processing, with hands-on experience packaging and integrating ML services into real applications

- Advanced experience with GenAI tools, LLMs (Claude, GPT, and others), and code generation tools such as GitHub Copilot or Windsurf

- Working knowledge of agentic AI frameworks such as LangGraph or CrewAI, MCP for tool and context integration, and familiarity with decision-making and planning frameworks

- Proven experience with cloud-based AI/ML services on AWS, Azure, or GCP, and solid understanding of the full AI/ML project lifecycle

- Familiarity with CI/CD/CT practices for ML systems and workflow orchestration tools such as Kubeflow or Airflow

- Master's or Ph. D. degree in Computer Science or a related field

- Strong interpersonal, analytical, and problem-solving skills

- Upper-intermediate or higher proficiency in English, both spoken and written