As a AI Engineer, your role typically involves programming. You would be responsible for the commitments in terms of time, effort and quality of work. You would likely be a part of a larger offshore team and are expected to work collaboratively with your peers onsite and offshore to deliver milestone/sprint-based deliverables.

Typical activities that would be expected are

- Program and deliver as per the scope provided by the delivery leads/onsite managers.

- Actively participate in the discussions/scrum meetings to comprehend and understand your scope of work and deliver as per your estimates/commitments

- Proactively reach out to others when you need assistance and to showcase your work

- Work independently on your assigned work

Requirements

Should have experience in the below:

- Python (Advanced proficiency)

- PyTorch / TensorFlow (Model Development & Deployment)

- LangChain / LlamaIndex (LLM Orchestration)

- HuggingFace Transformers

- OpenAI, AWS Bedrock, Vertex AI, or Azure OpenAI APIs

- Vector Databases for RAG (Weaviate / Milvus / FAISS/mongodb)

- MongoDB / PostgreSQL (Structured Data Retrieval & Joins)

- Redis / DynamoDB (Rapid Caching & Lookup)

- Kafka / RabbitMQ (Message Queues for Real-Time Inference)

- FastAPI / Flask (Backend APIs for ML Serving)

- Docker (Containerization for Model Inference)

- CI/CD Pipelines (GitHub Actions / GitLab CI / Jenkins)

- MLflow / Weights & Biases (Experiment Tracking & Model Management)

- S3 / GCS (Storage for Model Artifacts & Datasets)





- ElasticSearch / OpenSearch (Search over structured/unstructured text)

- Linting & Testing: Pytest, Black, Ruff, Flake8

- Type Hinting, Documentation Standards, YAML/JSON Config Management

- LLM training - finetuning (PEFT), pre-training

- Should be familiar with at least two Gen AI platform like Amazon Bedrock, Copilot, Vertex, etc..

- Should be familiar with at least two model like Claude, ChatGPT, Gemini, etc..

- Should be familiar with RAG Model and Agentic AI model

Architectural Requirements:

- Strong understanding of AI system design: data ingestion → preprocessing → model → retrieval → response

- Experience leading teams on LLM/NLP/ML projects end-to-end

- Excellent architectural decision-making & scalability mindset

- Familiarity with prompt engineering, evaluation metrics, and benchmarking

- Strong communication, documentation, and client-handling skills

Benefits

- Insurance benefits for the self and the spouse, including maternity benefits.

- Ability to work on many products as the organization is focused on working with several ISVs.

- Monthly sessions to understand the directions of each function and an opportunity to interact with the entire hierarchy of the organization.

- Celebrations are a common place - physical or virtual. Participate in several games with your coworkers.

- Voice your opinions on topics other than your work - Chimera Talks.

- Hybrid working models - Remote + office

📌 AI Engineer (Bengaluru)
🏢 Nameless
📍 Bengaluru