Lead AIML Engineer

otsi-global; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Object Technology Solutions, Inc (OTSI) in Hyderabad seeks a Lead Agentic AI Engineer to drive architecture and hands-on development of agentic AI systems. You will design multi-tenant cloud-native SaaS platforms on AWS/Azure/GCP, implement RAG and function calling, and lead governance, security, and compliance initiatives.

You will mentor teams, collaborate with product and customers, and advance observability and reliability across AI pipelines, ensuring scalable, production-grade deployments.

Qualifications

• 10+ years of software/AI engineering experience

Responsibilities

• Provide technical leadership and architecture for enterprise-grade agentic AI workflows.

Skills

Python development

AI/ML engineering

Generative AI

LLM integration

Agentic AI architectures

Cloud platforms

DevOps tooling

Tools

LangGraph

AutoGen

CrewAI

Semantic Kernel

AWS Bedrock

Azure AI Foundry

Vertex AI

Pinecone

Weaviate

Qdrant

pgvector

Docker

Kubernetes

GitHub Actions

Terraform

Job description

Object Technology Solutions, Inc (OTSI) has an immediate opening for a Lead Agentic AI Engineer. Lead Agentic AI Engineer (Hyderabad) Experience: 10+ Years

Technical Leadership & Architecture

Lead the design, development, and optimization of enterprise-grade agentic AI workflows. Architect scalable, secure, and multi-tenant SaaS platforms on public cloud environments (AWS/Azure/GCP). Define best practices for LLM integration, agent orchestration, and AI application architecture. Drive technical strategy for AI-powered products and accelerators.

Hands-on AI Engineering

Build and deploy agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, Agno, or Semantic Kernel. Integrate Large Language Models (LLMs) using AWS Bedrock, Azure AI Foundry, Vertex AI, and other AI platforms. Implement Retrieval-Augmented Generation (RAG), function calling, structured extraction, and intelligent document processing solutions. Develop Model Context Protocol (MCP) servers and enterprise AI integrations. Design and implement human-in-the-loop workflows for AI decision-making systems. Build PII detection, anonymization, and de-anonymization pipelines.

Security, Governance & Compliance

Establish LLM governance practices including cost optimization, rate limiting, monitoring, and audit trails. Implement AI guardrails against prompt injection, data leakage, and hallucination risks. Ensure compliance with security standards such as ISO 27001, SOC 2, PCI DSS, and enterprise security policies. Design secure AI solutions with appropriate access controls and data protection mechanisms.

Cloud & SaaS Engineering

Develop cloud-native AI applications using AWS, Azure, or GCP services. Design scalable multi-tenant SaaS architectures. Work with containerization and orchestration technologies including Docker and Kubernetes. Implement CI/CD automation using GitHub Actions, Terraform, or similar DevOps tools.

Customer & Sales Enablement

Participate in customer technical discovery sessions and solution discussions. Support sales teams with technical demonstrations, RFP/RFI responses, and AI solution proposals. Translate customer requirements and feedback into product enhancements.

Mentorship & Collaboration

Mentor engineering teams on agentic AI architecture, LLM development practices, and AI engineering standards. Collaborate with product, engineering, and customer teams to deliver innovative AI solutions. Drive best practices in AI observability, tracing, reliability, and compliance.

SKILLS AND ABILITIES REQUIRED

Strong experience in software engineering with expertise in Python development. Hands-on experience building production-grade AI/ML and Generative AI applications. Strong knowledge of Agentic AI frameworks: LangGraph AutoGen CrewAI Agno Semantic Kernel Experience integrating LLM platforms: AWS Bedrock Azure AI Foundry Vertex AI Strong understanding of: Retrieval-Augmented Generation (RAG) Prompt Engineering Function Calling Structured Data Extraction Intelligent Document Processing Experience with vector databases: Pinecone Weaviate Qdrant pgvector Hands-on experience developing MCP (Model Context Protocol) servers. Experience with AI security, governance, and guardrail frameworks: NeMo Guardrails Guardrails AI PII detection and redaction Strong understanding of cloud platforms: AWS (EKS, Lambda, S3, RDS) Azure / GCP Experience designing and implementing multi-tenant SaaS platforms. Knowledge of databases: SQL Object Storage Vector Databases