Generative AI Engineer

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About a21.ai

a21.ai is at the forefront of AI innovation, helping companies build large language model (LLM) applications and bespoke GenAI solutions. We are dedicated to delivering scalable, secure, and data-confidential AI solutions that cater to a diverse range of industries, including CPG, retail, and finance. As we continue to grow, we are seeking talented and enthusiastic fresh graduates to join our AI engineering team and contribute to cutting-edge artificial intelligence projects.

Job Summary

We are looking for passionate candidates with 2-5 years of experience who are excited about artificial intelligence and machine learning. The ideal candidate should have a strong background in building agentic AI systems, RAG pipelines, and implementing vector search solutions that solve real business problems.

This is a hands-on role with exposure to cutting-edge models, orchestration frameworks, and enterprise-scale deployments. You will work alongside experienced AI engineers and data scientists to develop, deploy, and optimize AI models and solutions that solve real-world business problems.

Key Responsibilities

• Design and implement

  multi-LLM agentic systems

  using frameworks like LangGraph, LangChain, or custom orchestration.
• Build and optimize

  RAG pipelines

  with vector databases (Pinecone, Qdrant, OpenSearch, Weaviate, FAISS).
• Engineer

  context injection and retrieval infra

  for domain-specific GenAI solutions.
• Collaborate with Data Engineers on

  embedding stores and unstructured data ingestion pipelines

  .
• Fine-tune or adapt

  transformer-based models

  for domain-specific tasks when required.
• Deploy solutions across

  cloud and on-prem environments

  , ensuring security, latency, and scalability.
• Work on

  client-facing projects

  , translating business problems into technical architectures.
• Stay updated with the latest AI research papers and industry trends

Technical Skills

• Strong programming in

  Python

  with hands-on experience in

  transformer libraries

  (Hugging Face, OpenAI, Anthropic, Llama).
• Experience with

  LangChain/LangGraph

  or similar orchestration frameworks.
• Hands-on expertise with

  Vector DBs and embedding pipelines

  .
• Knowledge of

  RAG system design

  and best practices.
• Experience with

  containerization & orchestration

  (Docker, Kubernetes).
• Ability to design solutions that are

  cloud-agnostic and on-prem deployable

  .

• Experience

  with version control systems (Git)

Soft Skills

• Strong analytical thinking and problem-solving abilities
• Eagerness to learn and adapt to rapidly evolving AI technologies
• Excellent communication skills to explain complex AI concepts to diverse stakeholders
• Collaborative mindset and ability to work in cross-functional teams
• Curiosity about AI research and willingness to experiment with new approaches
• Attention to detail and systematic approach to experimentation

Preferred Skills (Good to Have - Not Mandatory)

• Prior work with fine-tuning transformers or domain adaptation.
• Familiarity with observability and monitoring for LLM applications.
• Exposure to multi-agent systems and reinforcement learning concepts.
• Experience integrating AI into enterprise workflows/CRMs/ERPs.
• Basic understanding of cloud platforms (AWS, Azure, Google Cloud) and their AI services
• Knowledge of containerization technologies (Docker)
• Participation in ML competitions (Kaggle, hackathons) or research publications
• Understanding of MLOps concepts and tools

What We Offer

Learning & Growth

• AI Mentorship Program

  with dedicated senior AI engineers and researchers

• Comprehensive training

  on LLMs, GenAI, and production ML systems

• Research opportunities

  to work on cutting-edge AI projects and potentially publish papers

• Conference and workshop attendance

  to stay current with AI advancements

• Learning budget

  for AI/ML courses, certifications, and books

Technical Environment

• State-of-the-art AI tools

  and development environments

• Collaborative research culture

  with opportunities to contribute to open-source projects

• Innovation time

  (20%) to explore personal AI research interests

• Direct exposure

  to enterprise AI deployment challenges and solutions

Work Environment

Startup culture

Cross-functional collaboration

Regular tech talks

a21.ai is an equal opportunity employer.