Manager | AI / ML | Bengaluru | Artificial Intelligence & Data | AI Insights & Engagement

Deloitte & Touche GmbH Wirtschaftsprüfungsgesellschaft; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Deloitte & Touche GmbH Wirtschaftsprüfungsgesellschaft in Bengaluru seeks a Lead Software Engineer to design, build, deploy, and operate enterprise AI platforms and Agentic AI solutions. You will lead multi-agent systems, RAG, LLMs, and private environments, while mentoring teams and ensuring secure, scalable infrastructure across cloud and on‑prem environments.

The role emphasizes Python engineering, cloud-native platforms, DevOps practices, and governance.

Qualifications

• 7+ years in software engineering with Python.

Responsibilities

• Lead design, development, deployment of enterprise AI platforms.
• Develop and operate AI-powered applications and services.
• Mentor engineers and promote best practices in AI engineering.
• Ensure governance, security, and compliance for AI systems.
• Drive adoption of responsible AI and model governance.

Skills

Python engineering

REST APIs

Microservices

Agentic AI

Generative AI

DevOps

Terraform

Kubernetes

CI/CD

Security

Education

Bachelor's/Master's in CS/Eng

Tools

LangChain

LangGraph

CrewAI

AutoGen

Semantic Kernel

OpenAI APIs

Ollama

Hugging Face Transformers

Text Generation Inference

Job description

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Job Title: Manager | AI / ML | Bengaluru | Artificial Intelligence & Data | AI Insights & Engagement

Consultant Software engineer - Python, Agentic AI & AI Platform Engineering

Role Overview

We are seeking an experienced Lead Software Engineer - Python, Agentic AI & AI Platform Engineering to lead the design, development, deployment, and operation of enterprise AI platforms and intelligent automation solutions.

The ideal candidate should possess strong expertise in Python engineering, cloud-native platforms, DevOps practices, and hands‑on experience building and deploying Agentic AI solutions, AI Copilots, RAG frameworks, and private/local LLM environments. This role will work closely with Architecture, Security, Infrastructure, and Business teams to develop secure, scalable, and governed AI solutions for the organization.

Key Responsibilities

AI Platform Engineering & Agentic AI

• · Design, develop, and operate enterprise AI platforms supporting Generative AI, Agentic AI, AI Copilots, and intelligent automation use cases.
• · Build and deploy AI-powered applications using modern Agentic AI frameworks and architectures.
• · Design and implement multi-agent systems capable of reasoning, planning, tool calling, workflow execution, and human-in-the-loop interactions.
• · Develop Retrieval-Augmented Generation (RAG) solutions integrated with enterprise knowledge repositories and data sources.
• · Deploy and manage private/local AI environments using open-source LLMs and enterprise-grade AI platforms.
• · Design reusable AI services, APIs, agent frameworks, orchestration pipelines, and governance controls.
• · Collaborate with business stakeholders to identify automation opportunities and AI-driven process improvements.
• · Drive adoption of responsible AI, model governance, security, and compliance best practices.

Software Engineering & Platform Development

• · Develop scalable backend services and REST APIs using Python.
• · Build and maintain cloud-native and on‑premise solutions supporting AI and enterprise applications.
• · Lead code reviews and ensure adherence to engineering standards, security requirements, and architectural guidelines.
• · Build reusable software components and automation frameworks.
• · Mentor engineers and promote best practices across development teams.
• · Design, implement, and maintain highly available, secure, and scalable infrastructure platforms across cloud and on‑premises environments.
• · Drive Infrastructure as Code (IaC) practices using Terraform, Ansible, Kubernetes, and Vault.
• · Build and optimize CI/CD pipelines to enable reliable and automated software delivery.
• · Implement monitoring, alerting, logging, observability, and self‑healing mechanisms for critical platforms.
• · Support production environments through system design reviews, capacity planning, release governance, and operational excellence initiatives.
• · Participate in production support and escalation management as part of the engineering leadership team.

Required Skills & Qualifications

Core Engineering Skills

• · 7+ years of software engineering experience with strong expertise in Python.
• · Strong experience designing and developing REST APIs and microservices.
• · Experience with modern software engineering practices, design patterns, testing, and secure coding principles.

Agentic AI & Generative AI

• · Hands‑on experience designing and implementing Agentic AI solutions in enterprise environments.
• · Experience building AI applications using one or more of:
• o LangChain
• o LangGraph
• o CrewAI
• o AutoGen
• o Semantic Kernel
• o OpenAI APIs
• · Experience building:
• o AI Agents
• o Multi-Agent Systems
• o Conversational AI Solutions
• o Workflow Automation Agents
• o Knowledge Management Assistants
• · Strong understanding of:
• o Prompt Engineering
• o Tool Calling
• o Function Calling
• o AI Evaluation Frameworks
• o AI Guardrails

Private AI / Local LLM Experience

Hands‑on experience with at least one of the following:

• · Ollama
• · Hugging Face Transformers
• · Text Generation Inference (TGI)

Experience deploying and managing open‑source models such as:

• · Llama

Understanding of:

• · GPU-enabled infrastructure
• · Model hosting and inference optimization
• · Model lifecycle management
• · AI platform security and governance

Data & AI Platform Skills

Experience with Vector Databases such as:

Knowledge of:

• · Semantic Search

Strong experience with:

• · AWS and/or Microsoft Azure
• · GitHub Actions / GitLab CI / Azure DevOps

Working knowledge of:

• · Monitoring & Observability
• · Cloud Security
• · CI/CD and Release Engineering

Additional Skills (Preferred)

• · Experience working within Banking or Financial Services environments.
• · Exposure to AI governance, model risk management, and regulatory compliance frameworks.
• · Experience implementing enterprise AI Copilot solutions.
• · Lead technical discussions and architecture reviews.
• · Mentor and coach engineering teams on AI engineering, automation, and cloud-native development.
• · Drive innovation and adoption of emerging AI technologies.
• · Collaborate effectively across global teams and stakeholders.
• · Promote a culture of operational excellence, ownership, and continuous improvement.

Education & Experience

• · Bachelor's or Master's Degree in Computer Science, Engineering, Information Technology, MCA, or related discipline.
• · 7+ years of experience in Software Engineering, Platform Engineering, DevOps, or Infrastructure Automation.
• · Minimum 2+ years of hands‑on experience delivering Generative AI, Agentic AI, AI Copilot, or enterprise AI platform solutions.
• · Experience working in large-scale, mission‑critical, 24x7 enterprise environments.

Ideal Candidate Profile

We are looking for an engineer who has actually built and deployed AI agents and private AI platforms, not just experimented with GenAI tools. The ideal candidate should be equally comfortable developing Python applications, deploying local LLMs, building RAG and Agentic AI solutions, and operating secure enterprise‑grade platforms at scale.