AI Engineer

Job Description 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 (Fast 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 Requirements Strong hands-on experience in Javascript, Spring Boot, micro-services, JPA and JPQL Strong design, development and performance tuning skills on databases such as DB2, or any other RDBS. Experienced in technology stack selection and the definition of solution, technology and integration architectures for mid to large sized applications and cloud hosted platforms Strong understanding of various design and architecture patterns. Must have worked on desktop application development. Exposure to debugging and troubleshooting complex issues related to memory management, multi-threaded applications, custom messaging systems etc. Experience of implementing and governing software engineering processes, practices, tools and standards for development teams(such as clean code concepts) Full SDLC experience leveraging Agile, TDD and BDD for building and rolling out highly transactional and highly available platforms hosted on-premise and on the cloud Proficient in effort estimation techniques; will actively support Leads and scrum masters on planning the implementation and will work with test leads on the definition of an appropriate test strategy for the realization of a quality solution Must be hands on technology and able to troubleshoot critical issues in design or code Familiarity with CI/CD pipelines, DevOps practices, and version control systems like Git. Understanding of containerization tools like Docker and Kubernetes. Proven experience leading and managing software development teams. Strong project management abilities, including planning, tracking, and delivering on time. Experience in stakeholder communication and reporting project status to senior management.