Senior AI Engineer (1 Position)

About the Role

Senior AI Engineer

AI/ML expertise, software engineering skills, and product thinking

Key Responsibilities

• AI Application Development

  Design and build

  end-to-end AI applications

  , including prompt engineering, chaining, and orchestration.
• Implement

  agentic AI systems

  that can reason, plan, and execute workflows.
• Integrate AI with existing enterprise workflows and systems.

• LLMs and RAG Pipelines

  Develop

  RAG pipelines (embedding, vector search, retrieval)

  for contextual, domain-specific AI applications.
• Work with

  LLM APIs and open-source models (OpenAI, Anthropic, Llama, etc.)

  , and fine-tune or adapt models to domain requirements.
• Optimize context injection, prompt construction, and multi-turn conversational flows.

• Model Evaluation & Refinement

  Continuously

  evaluate AI model outputs

  and refine performance through prompt tuning, fine-tuning, and RLHF or similar techniques.
• Establish automated pipelines for

  model monitoring, feedback collection, and iterative improvements

  .

• Platform & Engineering

  Work with vector databases (pgvector, Pinecone, Weaviate, etc.), knowledge graphs, and embeddings at scale.
• Build

  API endpoints and microservices

  that expose AI capabilities in a scalable, production-grade manner.
• Ensure

  observability, logging, versioning, and A/B testing

  for AI services.

• Collaboration

  Collaborate with

  product managers, data engineers, and software engineers

  to define AI-driven features.
• Stay current with

  emerging trends in AI/ML, LLM architectures, and multi-agent systems

  .

Required Skills and Qualifications

• Core Expertise

  Minimum

  5+ years of experience in AI/ML engineering

  with a focus on applied AI solutions.

• Hands-on experience with LLMs (OpenAI, Anthropic, Hugging Face, etc.) and prompt engineering.

• Strong experience building

  RAG pipelines with embeddings and vector search

  .

• Software Engineering

  Proficiency in

  Python (FastAPI/Flask), or Java/Spring Boot for AI service development

  .
• Knowledge of

  microservices, APIs, and cloud-native architectures (AWS/GCP/Azure)

  .

• Data & Vector Systems

  Familiarity with

  pgvector, Pinecone, Weaviate, Milvus, or similar vector databases

  .
• Experience with data preprocessing, cleaning, and knowledge management for AI applications.

• AI Ops & Lifecycle

  Strong understanding of

  MLOps/LLMOps principles

  : model deployment, monitoring, retraining, and lifecycle management.
• Ability to

  evaluate AI outputs and incorporate feedback loops

  for model improvement.

• Soft Skills

  Problem-solving, analytical thinking, and a passion for innovation.
• Excellent communication and collaboration skills.
  

Preferred Qualifications

• Experience building

  agentic AI systems or autonomous multi-agent workflows

  .
• Exposure to

  knowledge graphs and reasoning systems

  .
• Background in

  NLP, transformers, embeddings, and vector similarity search

  .
• Contributions to

  open-source AI/ML projects

  .

Education

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or a related field.
  

What We Offer

• Opportunity to

  build an AI platform from the ground up

  , shaping the future of enterprise AI.
• Work with cutting-edge AI technologies and research.
• Competitive compensation and benefits.
• A collaborative environment that values innovation and experimentation.