Applied AI Platform Engineer (Performance Engineer) - Lead SDET I

Deloitte Development LLC; Hyderabad; Hybrid; INR 3,500,000 - 6,500,000; Full time

Job summary

Deloitte Development LLC is seeking an Applied AI Platform Engineer (Performance Engineer) - Lead SDET I to drive platform capabilities for AI engineering at scale. You will build tooling, accelerators, and frameworks used by multiple teams, mentoring others and raising engineering standards.

The role focuses on cross-functional collaboration, delivering reusable, scalable solutions across Deloitte’s AI initiatives and data infrastructure, with hands-on leadership and technical excellence.

Qualifications

• A bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline.
• Experience is the most relevant factor for this role.
• Hands-on experience with Performance Engineering is important.
• 10+ years of software and platform engineering experience with listed technologies.

Skills

Angular

React

NodeJS

Python

C#

Java

Rust

SQL/NoSQL

PyTorch

TensorFlow

LangChain

LangGraph

LangSmith

LangFuse

Terraform

Testing frameworks

Education

Bachelor's degree in computer science, software engineering, data science, machine learning, or related discipline

Tools

Kubernetes

Docker

Databricks

CI/CD

ArgoCD

GitHub

SonarQube

OpenAI

Vertex AI

Job description

Applied AI Platform Engineer (Performance Engineer) - Lead SDET I

Role Overview:

As an Applied AI Platform Engineer (Performance Engineer) - Lead SDET I, you will actively engage in your engineering craft, taking a hands-on approach to building the platforms, tooling, accelerators, and frameworks that other engineering teams build on. Your expertise will be pivotal in delivering platform capabilities that delight the engineers who depend on them, while driving tangible leverage and value across Deloitte’s AI engineering investments. You will leverage your extensive engineering craftsmanship and advanced proficiency across platform engineering, distributed systems, and modern AI/ML and Data infrastructure, consistently demonstrating your exemplary track record in delivering high-quality, reusable, outcome-focused solutions. The ideal candidate will be a role-model leader and mentor, collaborating with cross-functional teams to design, build, and operate the enabling layer for AI engineering at scale.

The team:

US Deloitte Technology Product Engineering has modernized software and product delivery, creating a scalable, cost-effective model that focuses on value/outcomes that leverages a progressive and responsive talent structure. As Deloitte’s primary internal development team, Product Engineering delivers innovative digital solutions to businesses, service lines, and internal operations with proven bottom-line results and outcomes. It helps power Deloitte’s success. It is the engine that drives Deloitte, serving many of the world’s largest, most respected companies. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.

The successful candidate will possess:

• Excellent interpersonal and organizational skills, with the ability to handle diverse situations, complex projects, and changing priorities, behaving with passion, empathy, and care.

Required Qualifications:

• A bachelor’s degree in computer science, software engineering, data science, machine learning, or related discipline. Experience is the most relevant factor.

Hands On experience with Performance Engineering is important.

• 10+ years of software and platform engineering experience with most of the following: Angular, React, NodeJS, Python(Mandatory), , C#, .NET, Java, Rust, SQL/NoSQL, PyTorch, TensorFlow, LangChain, LangGraph, LangSmith, LangFuse, Terraform, as well as unit, integration, and end-to-end testing frameworks & tools, specifically BDD, Gherkin, Cucumber, Playwright, and Selenium.


• 3+ years of experience designing, building, and operating AI/ML platform or infrastructure, with hands-on experience across building tooling for MLOps/LLMOps, model serving, retrieval and vector infrastructure, and eval/observability instrumentation for LLM integration (OpenAI, Anthropic, or open-source models).


• 3+ years of experience with cloud-native engineering on any of the cloud hyperscalers such as Azure, AWS, or GCP—including their AI/ML services such as Azure OpenAI, AWS Bedrock, or Vertex AI—as well as container orchestration (Kubernetes, Docker), Big Data, Databricks, CI/CD at platform scale, and distributed systems.


• 1+ years of experience establishing engineering standards and golden paths, including actively leading, mentoring, and guiding team members in the adoption and continuous improvement of these standards, treating the platform as a product.


• Prior experience with AI control-plane and agent-runtime patterns: model/LLM gateway, A2A and MCP integration, agent runtimes (e.g., Google ADK, Amazon Bedrock AgentCore), guardrails (PII redaction, prompt-injection, content, tool permissioning/tool-RBAC), policy-as-code, and multi-tenant isolation.


• Prior experience with enterprise data platform engineering: data pipelines, self-service and data-product enablement, governance-as-code enforcement, and metadata/lineage.


• Prior software engineering experience with the understanding of Business Context Diagrams (BCD), sequence/activity/state/entity relationship/data flow diagrams, OOP/OOD, data structures, algorithms, and code instrumentations, and AI-augmented spec-driven development.


• Prior experience using methodologies & tools such as XP, Lean, DevSecOps, SRE, ADO, GitHub, SonarQube, and ArgoCD to deliver high-quality platforms and products rapidly.

Other:

• Ability to travel 10%, on average, based on the work you do and products you build.


• Limited immigration sponsorship may be available.