AI Research Engineer

General Summary:

The AI Research Engineer is responsible for designing and implementing intelligent, scalable AI solutions with a focus on agentic AI, Retrieval-Augmented Generation (RAG) and Modular Cognitive Processes (MCP). This role is ideal for individuals who are passionate about research and development in the space of agentic AI and has demonstrated experience in building complex AI solutions. The research engineer will collaborate with cross-functional teams to deliver high-quality, production-ready AI systems aligned with business goals and technical standards

Essential Duties & Responsibilities:

Investigate and apply emerging technologies to address complex, non-trivial problems.

Oversee the design and development of entire components or subsystems.

Build and maintain scalable data pipelines and services to support AI workflows.

Develop algorithms and systems for information retrieval, machine learning, information extraction, text categorization, text mining, and related areas within large online delivery environments.

Collaborate with product and engineering teams to translate business needs into AI solutions.

Debug and optimize AI systems across the stack to ensure performance and reliability.

Stay current with emerging AI tools, libraries, and research, and integrate them into projects.

Contribute to the development of internal AI standards, reusable components, and best practices.

Apply MCP principles to design modular, intelligent agents capable of autonomous decision-making.

Work with vector databases, embeddings, and LLMs (e.g., GPT-4, Claude, Mistral) for intelligent retrieval and reasoning.

Participate in code reviews, testing, and validation of AI components using frameworks like pytest or unittest.

Document technical designs, workflows, and research findings for internal knowledge sharing.

Adapt quickly to evolving technologies and business requirements in a fast-paced environment.

Knowledge, Skills, and/or Abilities Required:

25 years of experience in AI/ML engineering, with a focus on agentic AI.

Passion for research and development in the field of agentic AI.

Proven experience in building agentic systems and complex AI solutions.

Strong Python programming skills with a solid foundation in OOP and software engineering principles.

Hands-on experience with AI frameworks such as LangChain, LlamaIndex, Haystack, or Hugging Face.

Familiarity with MCP (Modular Cognitive Processes) and their application in agent-based systems.

Experience with REST API development and deployment.

Proficiency in CI/CD tools and workflows (e.g., Git, Docker, Jenkins, Airflow).

Exposure to cloud platforms (AWS, Azure, or GCP) and services like S3, SageMaker, or Vertex AI.

Understanding of vector databases (e.g., OpenSearch, Pinecone, Weaviate) and embedding techniques.

Strong problem-solving skills and ability to work independently or in a team.

Interest in exploring and implementing cutting-edge AI tools and technologies.

Ability to communicate technical concepts clearly to both technical and non-technical audiences.

Educational/Vocational/Previous Experience Recommendations:

Bachelor/ Master degree in CS or related field.

1+ years of relevant experience