Senior AI Engineer

Artifact Corporation; Hyderabad; Hybrid; INR 3,600,000 - 7,000,000; Full time

Benefits offered by this job

Health insurance

Certification & learning budget

Direct access to frontier models

Job summary

Microcare, Hyderabad, is seeking a founding senior AI engineer to translate customer AI conversations into deployed systems. You will own end-to-end solutions—model choice, data ingestion, training, deployment and hand-over—primarily on on-prem NVIDIA GPU clusters or private clouds.

You will build scalable AI components like an Organization GPT framework, enterprise document search, and AI labs enablement, collaborating with customers and partners to shape offerings.

Qualifications

• Proficient Python and framework knowledge (FastAPI or equivalent).
• Strong SQL, Git, and software engineering fundamentals.
• Hands-on RAG, embeddings, and vector databases.
• Experience with LangChain, LlamaIndex or equivalent.
• Exposure to major LLM APIs (Claude/OpenAI/Azure/B Bedrock).
• Docker and Kubernetes deployment on Linux (on-prem or cloud).
• Document processing: PDF parsing, OCR, table extraction.

Responsibilities

• Design and build GenAI applications including RAG pipelines, chat agents, and tool-using agents across platforms (Claude, OpenAI, Azure OpenAI, AWS Bedrock, open-weight models).
• Own the organization GPT framework end-to-end: ingestion, chunking, embeddings, vector search, prompts, model orchestration, access control and audit logs.
• Deploy and serve models on on-prem GPUs with vLLM/TGI/Triton; manage GPU sizing for workloads.
• Fine-tune and evaluate models (LoRA/QLoRA) including Indian languages (Telugu, Hindi).
• Build evaluation and guardrails: retrieval quality, hallucination checks, red-teaming, PII handling, data residency per DPDP and RBI rules.
• Lead technical discovery, write architectures and estimates, support pre-sales for proposals and tenders.
• Mentor engineers, review code, and raise engineering standards; contribute to AI lab curricula.

Skills

Python

FastAPI

SQL

Git

LangChain

LlamaIndex

Embeddings

Vector databases

LLM APIs

Docker

Kubernetes

Linux

ML/GenAI production

Education

B.Tech/B.E., M.Tech or MCA in Computer Science

Bachelor/Master in CS/CE/SE

Tools

Docker

Kubernetes

Linux

Job description

Location - Hyderabad, Telangana (on-site / hybrid; travel to customer sites in AP and Telangana).

Experience - (6 –10 ) years in software engineering, with 3+ years building ML/GenAI systems in production.

Employment - Full-time opportunity.

Reports to - Head, AI Practice Team, Team - AI Solutions & AI Labs practice.

About Microcare

Microcare is a 37-year-old IT systems integrator headquartered in Hyderabad, with 350+ people and engineers across five locations in Andhra Pradesh and Telangana. We have served 700+ customers and delivered 2,000+ projects.

We are an HPE Platinum Partner, a Microsoft Solutions and Cloud Partner, an AWS Partner, and partners of Anthropic (Claude) and OpenAI (ChatGPT). Our AI practice builds AI data centers, sets up AI labs, delivers AI solutions, and runs skill development programmes for enterprises, banks, government, and higher education.

The role -

You will be a founding senior engineer in Microcare's AI practice, turning customer AI conversations into working, deployed systems. Most of our customers need AI that runs on their own infrastructure — on-premise GPU clusters we build on HPE, or private cloud tenancies — so you will own solutions end to end, from model choice to production hand-over.

What you will build

• Organization GPT framework — a reusable, packaged platform we deploy as CampusGPT, BankGPT and other organization-specific assistants, on-prem or in cloud.
• Enterprise document search and RAG — secure retrieval over large document estates, starting with our AI document search MVP for a regional rural bank.
• AI lab enablement — the software stack, sample workloads and experiment support for the GPU labs we install at engineering colleges and enterprises.
• Government and enterprise AI solutions — agents, copilots and analytics delivered under empanelments and tenders.

Key responsibilities

• Design and build GenAI applications: RAG pipelines, conversational assistants, and tool-using agents on Claude, OpenAI, Azure OpenAI, AWS Bedrock and open-weight models (Llama, Mistral, Qwen).
• Own the core of the organization GPT framework — ingestion, chunking and embeddings, vector search, prompt and model orchestration, role-based access, audit logs — packaged for repeatable deployment.
• Deploy and serve models on on-prem NVIDIA GPU infrastructure (vLLM, TGI, Triton, Ollama) with Docker and Kubernetes; size GPU, memory and storage for customer workloads.
• Fine-tune and evaluate models (LoRA/QLoRA), including for Indian languages such as Telugu and Hindi where customers need it.
• Build evaluation and guardrails: retrieval quality, hallucination checks, red-teaming, PII handling, and data residency in line with India's DPDP Act and sector rules (RBI for banks).
• Lead technical discovery with customers, write solution architectures and effort estimates, and support pre-sales on proposals and tenders.
• Mentor junior engineers and freshers, review code, and set engineering standards for the AI practice.
• Contribute to AI lab curricula and skill development programmes.

Must-have qualifications

• B.Tech/B.E., M.Tech or MCA in Computer Science or a related field.
• 6+ years of software engineering, with 3+ years building ML or GenAI systems that reached production.
• Strong Python; working knowledge of FastAPI or similar, SQL, and Git.
• Hands-on RAG experience: LangChain, LlamaIndex or equivalent; embeddings; vector databases (pgvector, Milvus, Qdrant, Chroma or Elasticsearch).
• Experience with at least one major LLM API (Claude, OpenAI/Azure OpenAI, Bedrock or Gemini) and with open-weight models.
• Experience deploying with Docker and Kubernetes on Linux, on-prem or in cloud.
• Document processing: PDF parsing, OCR, table extraction across messy, scanned enterprise documents.
• Clear communication in English with customer technical teams; able to explain trade-offs to non-technical stakeholders.

Nice to have

• GPU serving and performance tuning: CUDA basics, quantization (GPTQ, AWQ, GGUF), multi-GPU inference.
• Agent frameworks and protocols: Model Context Protocol (MCP), LangGraph, CrewAI, or the Claude Agent SDK.
• Indic language NLP and speech (e.g. AI4Bharat models, Bhashini).
• Experience with HPE, NVIDIA or other enterprise GPU hardware, or with private cloud (OpenShift, VMware).
• Delivery for banking, government or higher-education customers in India.
• Cloud AI certifications (Azure AI Engineer, AWS ML Specialty, NVIDIA DLI).

What we offer

• A senior seat in a new AI practice, with real influence over architecture and the products we take to market.
• Direct access to frontier models and partner programmes from Anthropic, OpenAI, Microsoft, AWS and HPE.
• Hands-on work with on-prem GPU infrastructure that most engineers only see in the cloud.
• Competitive compensation, health insurance, and a certification and learning budget.