Top Artificial Intelligence Jobs in Gurgaon

Provides systems safety engineering for aircraft turbine engines and auxiliary power systems. Conducts hazard and safety analyses, develops safety requirements and documentation, supports FAA and EASA compliance, performs reliability analysis, and reviews designs. Collaborates across engineering teams on risk mitigation, corrective actions, and aftermarket safety metrics. The role also supports process standardization, automation, AI application, technical coaching, innovation, and strategies to reduce certification cycle time and cost.

Develop and maintain full-stack applications using React and Python. Collaborate effectively with the team, communicate clearly, take ownership of responsibilities, and work independently as a self-starter. The role requires working from Gurgaon three days per week and may involve technologies including GCP, machine learning, web services, Git, Power BI, Node.js, Power Apps, and REST services.

Designs and oversees enterprise software architecture, development, testing, implementation, and technical documentation. Partners with stakeholders and Product teams to define requirements, evaluate technologies, create scalable solutions, review code, support application integrations, and guide development teams. The role also coordinates technology projects, training, system improvements, security, quality, and extensibility while providing technical support for case and client efforts.

Develop and ship Yahoo Mail mobile features for Android, owning projects from technical design through deployment, monitoring, and improvement. Build scalable solutions using Kotlin, Java, Android frameworks, Jetpack Compose, and React Native; integrate APIs; address performance, reliability, and usability challenges; conduct code reviews; collaborate cross-functionally; mentor teammates; and use AI development tools to improve engineering productivity while maintaining quality and security.

Design and scale cloud and Kubernetes infrastructure, distributed systems, CI/CD, observability, and deployment tooling. Build production-grade AI agents for infrastructure and engineering workflows, including tool use, evaluation, permissions, guardrails, and failure handling. Improve reliability, performance, and cloud efficiency; troubleshoot across application and infrastructure layers; mentor engineers; document architecture; and participate in on-call operations.

Lead the architecture, development, deployment, and maintenance of scalable Java backend services and APIs for AI-powered platforms. Integrate machine learning models into production through APIs and data pipelines, enforce testing and CI/CD best practices, conduct code reviews, and guide technical delivery. Collaborate with product, data science, and engineering teams while evaluating emerging backend, AI, and machine learning technologies.

Lead enterprise architecture strategy for a global financial institution. Review fraud-domain application portfolios, assess architecture options and build-versus-buy decisions, conduct rationalization assessments, define target-state “north star” architectures, and create estimates, roadmaps, and transition architecture diagrams. Serve as a technical authority while translating complex business challenges into scalable solutions and collaborating with technical and business stakeholders.

Leads end-to-end power, performance, and area optimization for AI semiconductor SoCs. Influences architecture, RTL, memory hierarchies, dataflows, floorplanning, multi-voltage domains, synthesis, placement, clock-tree synthesis, routing, and power-analysis workflows. Partners with architecture, RTL, physical design, EDA vendors, and software teams to develop custom methodologies and deliver energy-efficient silicon under stringent PPA constraints.

Develop scalable Node.js software and highly available RESTful and GraphQL APIs. Build and maintain microservices, work with databases and cloud platforms, write automated tests, troubleshoot and tune performance, and uphold security, coding, documentation, and review standards. Collaborate with product and delivery teams, contribute to architecture and technical decisions, and deliver software in an agile environment.

Provides systems safety engineering for aircraft turbine engines and power systems. Conducts hazard, reliability, and root cause analyses; develops safety requirements, plans, procedures, and reports; reviews designs for regulatory compliance; manages requirements using DOORS; supports certification and qualification; collaborates cross-functionally on risk mitigation, reliability metrics, process automation, and AI-enabled safety improvements.

As an AI Architect, you will lead AI strategy, design and implement AI systems, oversee model evaluation, and ensure data ethics, driving innovation in a collaborative environment.

Provides technical leadership for FAA and EASA certification and qualification of aircraft turbine engines and auxiliary power units. Prepares and reviews certification and qualification plans, reports, and related artifacts; coordinates with aviation regulators; standardizes and improves certification processes; and applies automation and artificial intelligence to reduce cycle time and cost. Supports systems engineering activities, talent development, technical coaching, and innovation across Honeywell Aerospace programs.

Designs and develops scalable automated testing solutions for carrier-grade, cloud-native network products. Responsibilities include building functional, regression, performance, and end-to-end test frameworks; developing tests with Python, Java, or Go; integrating testing into CI/CD pipelines; applying AI/ML for test generation and defect analysis; analyzing network and test data; and collaborating with development, product, and QA teams.

Designs and develops scalable automated testing solutions for carrier-grade, cloud-native network products. Responsibilities include building functional, regression, performance, and end-to-end test suites; integrating testing into CI/CD pipelines; applying AI/ML for test generation, anomaly detection, defect prediction, and self-healing automation; analyzing network and test data; and collaborating with development, product, and QA teams.

Lead and mentor 5–10 technical trainers creating and evaluating terminal-based AI training tasks. Review software, computational, electrical engineering, circuit, HDL, simulation, and automated grading tasks for correctness, reproducibility, numerical accuracy, performance, and reliability. Identify flawed assumptions, nondeterminism, race conditions, testing weaknesses, and technical inaccuracies. Allocate work, resolve blockers, provide detailed feedback, track revisions, and maintain technical documentation and quality standards.

The role involves developing full-stack web apps, creating APIs, improving lead capture models, and collaborating across teams to enhance the Social Planner product.

Design and build scalable AI agents, data pipelines, ETL/ELT processes, microservices, and data federation layers. Develop generative AI solutions using Google ADK and LLMs, integrate agentic AI tools, and support Data Mesh and cloud-native architectures. Ensure data quality, security, scalability, and regulatory compliance while advancing engineering standards and business-focused analytics platforms.

Own product features end-to-end, including architecture, integrations, technical specifications, deployment, testing, and production reliability. Use AI agents as the primary development tool, delegate implementation, critically review generated code, and ensure financial transaction reliability. Work independently as an individual contributor while helping evolve the company’s AI-first development process.

Own quality for AI products including a support chatbot, API Copilot, and MCP server. Build golden datasets, evaluation harnesses, scoring systems, regression coverage, and release gates. Analyze production traces and tool calls to identify hallucinations, retrieval, generation, tool-use, context, and PII failures. Define quality metrics, investigate root causes, and convert findings into actionable engineering evidence. The role requires Python, API testing, AI evaluation experience, and strong QA/SDET expertise.

Own the quality strategy and end-to-end testing pipeline for an AI-generated product handling real-money transactions. Build automated UI, browser, mobile, pre-merge, nightly, release, and production testing gates; integrate testing with CI/CD; evaluate external tools; and improve reliability of critical financial flows. The role partners with engineering and DevOps, uses AI coding agents daily, and drives quality initiatives as an autonomous individual contributor.

Designs and develops scalable cloud-based and serverless software across the company’s platform. Builds prototypes and production services, applies AI throughout the SDLC, promotes modern Agile and Well-Architected practices, troubleshoots customer and internal issues, develops comprehensive test suites, and coaches software engineers. The role requires extensive distributed application experience and backend expertise across multiple programming languages, databases, cloud technologies, integrations, and workflow orchestration.

Participate in full-stack development and maintenance of Binance’s KYC system, including backend services, frontend features, documentation, testing, regression, troubleshooting, and customer issue resolution. The role is a 3–6 month accelerator internship for current university students and recent graduates, with an emphasis on Java, Spring Boot, databases, middleware, and frontend technologies.

Build and ship core AI interface platform components connecting AI agents and developers to MongoDB (MCP Server, Agent Skills, Intelligent Assistant Platform). Define architecture, implement scalable backend services, own ambiguous projects end-to-end, mentor engineers, participate in on-call rotation, and collaborate across research, product, and design.

Perform requirements analysis, create test plans and cases, prepare test data, execute functional and regression testing, manage defects in Zoho Sprint, and conduct root-cause analysis. Validate databases with SQL and APIs using Postman and Swagger. Prepare quality reports and metrics, collaborate with developers, support releases, and identify AI opportunities to improve QA productivity. Automation experience with Playwright, Java, TestNG, Maven, scripting, and CI/CD is preferred.

Develop and maintain Python applications, APIs, workers, integrations, and AWS Lambda functions. Manage AWS and Linux environments, infrastructure automation, deployments, CI/CD pipelines, and production support. Improve reliability through monitoring, canary releases, rollback, and recovery practices. Maintain databases, messaging, authentication, security, dependencies, and external integrations. Apply AI-assisted development tools with human review and security validation. The role requires ownership of software delivery from application code through production.