Senior AI Engineer

InfraCents Pvt. Ltd.; India; Remote; INR 2,500,000 - 5,500,000; Full time

Job summary

InfraCents Pvt. Ltd. in India seeks a Senior AI Engineer to lead the design and delivery of AI systems for clients, from multi-step agents and enterprise RAG to fine-tuned and self-hosted models. You will make key architecture decisions, set evaluation standards and guide other engineers.

The role blends deep technical expertise with client engagement: shaping AI use cases, estimating effort and risk, and turning promising pilots into reliable, cost-effective production systems.

Qualifications

• 4–7 years in ML or software engineering with AI/LLM systems in production.
• Has designed AI systems that serve real users at scale.
• Comfortable across LLM apps, classical ML and infrastructure.

Responsibilities

• Design end-to-end AI architectures: retrieval, agents, tools, memory, guardrails and serving.
• Lead AI engagements from discovery to production rollout.
• Own quality, latency and cost targets, and report against them.
• Review designs and code, and unblock engineers on hard problems.

Skills

ML Engineering

Production ML

Technical Leadership

Client Engagement

System Architecture

Education

Bachelor's or Master's in CS/Engineering

Tools

LangGraph

LlamaIndex

Claude Agent SDK

OpenAI SDK

PyTorch

Hugging Face Transformers

Job description

About InfraCents

InfraCents is a software engineering company. We design and build software products, run the cloud platforms they live on, build AI systems and data pipelines, and keep all of it secure, reliable and cost-efficient in production. Our engineers work directly with clients, own outcomes end to end and are trusted with real production systems. We value clear thinking, honest communication and work that still holds up a year after it ships.

Role Overview

The Senior AI Engineer will lead the design and delivery of AI systems for clients, from multi-step agents and enterprise RAG to fine-tuned and self-hosted models. You will make the key architecture decisions, set evaluation standards and guide other engineers.

The role blends deep technical expertise with client engagement: shaping AI use cases, estimating effort and risk, and turning promising pilots into reliable, cost-effective production systems.

Key Responsibilities: Architecture & Technical Leadership

• Design end-to-end AI architectures: retrieval, agents, tools, memory, guardrails and serving.
• Choose between prompting, RAG, fine-tuning and classical ML based on evidence.
• Set standards for evaluation, AI observability and responsible AI across projects.

Key Responsibilities: Delivery

• Lead AI engagements from discovery and proof of concept through production rollout.
• Own quality, latency and cost targets, and report against them.
• Review designs and code, and unblock engineers on hard problems.

Key Responsibilities: Models & Infrastructure

• Fine-tune and adapt models (LoRA / QLoRA) where it is justified by evaluation.
• Deploy and scale model serving on GPUs, optimising throughput and cost.
• Secure AI systems: data access controls, tenant isolation, audit trails and prompt-injection defences.

Key Responsibilities: People & Client Engagement

• Mentor AI engineers and contribute to hiring.
• Run client discovery workshops, identify high-value AI use cases and prepare solution proposals.
• Contribute to case studies, technical blogs and thought leadership.

Who We're Looking For

• Experience: 4-7 years in ML or software engineering, with AI or LLM systems running in production.
• Architecture: Has designed AI systems that serve real users at scale.
• Breadth: Comfortable across LLM applications, classical ML and the infrastructure that runs them.
• Leadership: Has led a team or workstream and mentored engineers.
• Client exposure: Can lead technical conversations with client leadership and translate them into delivery plans.

Technical Expertise Required

• Models & Platforms: Claude, GPT, Gemini, Llama / Mistral / Qwen, AWS Bedrock, Azure OpenAI, Vertex AI
• Agents & Orchestration: LangGraph, LlamaIndex, Claude Agent SDK / OpenAI Agents SDK, MCP, Temporal
• Training & Fine-tuning: PyTorch, Hugging Face Transformers, PEFT (LoRA / QLoRA), Unsloth
• Serving & Infrastructure: vLLM, TGI / Triton, Ray, Kubernetes, GPU instances (AWS, GCP, Azure)
• Retrieval & Data: pgvector, Pinecone / Qdrant / Weaviate, OpenSearch, Kafka, Spark
• Evaluation & Observability: Langfuse / LangSmith, Ragas, promptfoo, OpenTelemetry, Arize Phoenix
• Engineering: Python, FastAPI, TypeScript, Docker, Terraform

Nice to Have

• Experience with AI governance and compliance (ISO 42001, EU AI Act, DPDP Act).
• Published research, open-source contributions or conference talks.
• Experience with speech, vision or multimodal systems.

Qualifications

• Experience: 4-7 years in ML or software engineering, with 2+ years building LLM or AI systems.
• Education: Bachelor's or Master's degree in Computer Science, Engineering or a related field, or equivalent practical experience.