Top Artificial Intelligence Jobs in Bangalore

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.

Design and maintain scalable backend services using Java and Spring Boot; build REST APIs, microservices, and event-driven systems; manage AWS infrastructure with Salt and Terraform; support observability, reliability, automation, incident response, and production operations. Collaborate cross-functionally, participate in architecture reviews, use AI-assisted development tools, and mentor engineers.

Develop scalable Python and Flask applications, APIs, Azure cloud solutions, data pipelines, PostgreSQL databases, Redis integrations, and front-end components. Build agentic AI solutions, automated Playwright tests, and CI/CD processes while supporting secure coding, performance optimization, code reviews, troubleshooting, and production operations. Collaborate with product, architecture, DevOps, and security teams in an Agile environment.

Build Python-based tools for layout, animation, matchmove, and previs artists working with complex CG scenes. Develop scene-management systems, asset and animation library integrations, and 3DEqualizer data import/export workflows. Collaborate with product owners and stakeholders in an Agile environment, contributing across design, development, maintenance, and pipeline integration. Work may include front-end and back-end development for high-end VFX and feature animation pipelines.

Lead enterprise architecture strategy and design scalable, resilient platforms spanning full-stack applications, AI/ML systems, distributed architectures, and cloud-native infrastructure. Architect RAG pipelines, integrations, CI/CD, DevOps automation, observability, and security governance. Drive scalability and performance optimization, establish technical standards, collaborate with stakeholders, review designs, and mentor engineering teams. The role requires extensive experience with Python, cloud platforms, React or similar frameworks, Docker, Kubernetes, microservices, event-driven systems, and enterprise architecture leadership.

Leads enterprise architecture strategy and designs scalable, resilient full-stack, AI/ML, and cloud-native platforms. Responsibilities include architecting RAG and agentic AI systems, defining integrations, driving CI/CD and DevOps automation, optimizing scalability and performance, establishing governance, mentoring engineers, and collaborating with stakeholders on solution architecture.

Develop and extend ServiceNow AI Control Tower for enterprise AI governance and lifecycle management. Build AI agents, skills, workflows, integrations, and secure access controls while managing CMDB/CSDM data. Configure plugins, scopes, dependencies, and governance policies; support AI Agent Fabric protocols and third-party AI platforms. Collaborate with governance, risk, compliance, and platform teams, and maintain scripts, workflows, version control, rollback, and quality assurance processes.

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, develop, and maintain a scalable threat intelligence platform using backend, frontend, cloud, database, and AI technologies. Collaborate with product, security, and engineering stakeholders to translate requirements into reliable software. Lead code quality practices, documentation, testing, CI/CD, and microservices development while mentoring software developers. Integrate AI agents and intelligent services into enterprise products, and guide teams on AI tooling, prompt engineering, and production evaluation.

Designs and supports enterprise DevOps platforms across on-premises and cloud environments. Responsibilities include CI/CD automation, Infrastructure as Code, Linux administration, hybrid cloud operations, Kubernetes platform management, AI/ML infrastructure support, monitoring, reliability engineering, production support, security, disaster recovery, and incident management. The role partners with infrastructure, application, security, architecture, and operations teams to deliver scalable, secure, and highly available platforms.

Leads a 50-person, multi-level manufacturing engineering organization supporting multiple business units and product lines. Owns OMS/iOMS delivery, manufacturing documentation readiness, NPI and high-volume manufacturing execution, operational performance, quality, productivity, and factory readiness. Establishes operating mechanisms, scorecards, risk reviews, and executive escalations while driving digital transformation through automation, AI, and model-based manufacturing. Partners with engineering, manufacturing, quality, supply chain, operations, suppliers, and global stakeholders.

Develop and run CFD simulations for refrigerant leaks, gas dispersion, ventilation, and fire/combustion scenarios (transient and steady). Model multiphase flows, species transport, ignition and flame propagation, analyze hazard scenarios, apply boundary conditions, support V&V against test data, produce technical reports, and collaborate with cross-functional teams on safety, compliance, and product design.

Design, develop, and deliver wireless and IoT software features for Cisco access points across embedded, controller, and cloud-integrated systems. Own features from requirements through field support, debug production software across embedded Linux, firmware, networking, protocol, and container layers, and make architectural decisions. Improve quality through testing, CI/CD, threat modeling, root-cause analysis, and AI-assisted development. Collaborate across engineering and customer-facing teams while mentoring junior engineers.

Leads architecture and hands-on development of scalable, secure, cloud-native enterprise applications, primarily backend services across the full stack. Owns complex initiatives from design through production, drives testing, observability, CI/CD, reliability, security, and cost optimization, and applies AI/ML and generative AI capabilities. Provides technical leadership, mentorship, architectural influence, and cross-functional collaboration.

Build and ship internal tools, backend services, APIs, frontend interfaces, data integrations, automation, and AI-powered features. Integrate LLM, RAG, and agent capabilities into usable software, collaborate with teams across the business, and own solutions through production. The role requires adaptable full-stack engineering, data fluency, AI integration experience, autonomy, and reliable end-to-end delivery.

Designs, builds, secures, automates, and operates enterprise Databricks platforms across development, testing, and production. Responsibilities include data pipeline integration, ML and generative AI enablement, CI/CD, Infrastructure as Code, governance, monitoring, reliability, cost optimization, and platform support. The role collaborates with engineering, security, architecture, and business teams while mentoring junior engineers and shaping platform standards and roadmaps.

Administer and optimize HPE PCAI and AI Factory AI/HPC infrastructure, including GPU clusters, container platforms, storage, networking, automation, observability, security, and AI workloads. Manage platform lifecycle, patching, monitoring, incident response, root-cause analysis, capacity planning, and operational improvements. Support NVIDIA AI Enterprise, Ezmeral platforms, Kubernetes, SLURM, and related development tools while mentoring support teams and coordinating with engineering.

Design, develop, debug, validate, and optimize software tools and algorithms supporting engineering domains including silicon design, manufacturing, validation, and systems integration. Collaborate across disciplines to improve engineering workflows, ensure high performance and reliability, apply secure coding practices, and enable effective integration of Intel silicon and software.

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.

Develops secure, scalable Java full-stack applications using Spring Boot, ReactJS, and AWS. Uses authorized AI coding tools and prompt engineering to improve development, testing, documentation, and productivity while validating outputs for security and quality. Contributes to architecture, analyzes data for application improvements, troubleshoots software components, and participates in agile engineering practices, CI/CD, resiliency, security, and technical communities.

Designs and maintains scalable QA automation frameworks and test suites for identity governance and AI-agent capabilities. Develops AI-driven testing for APIs, workflows, integrations, cloud systems, and end-to-end scenarios. Analyzes failures, automates defect detection, validates performance, security, reliability, observability, and compliance, and collaborates cross-functionally to improve release quality and test coverage.

Design and develop scalable Kubernetes platforms supporting microservices, AI/ML, LLM, and GPU workloads. Build backend services and infrastructure automation using Go or Python, implement IaC and CI/CD, improve observability and reliability, and support production ML workflows. Participate in on-call operations, incident response, code reviews, technical decision-making, and mentoring. Collaborate with SREs, data scientists, and engineering teams to optimize distributed systems and AI platforms.

Lead ServiceNow-focused enterprise architecture and governance, design scalable ServiceNow and AI-enabled automation solutions, drive architecture reviews and standards, identify process improvements and automation opportunities, collaborate with global teams, and advise on AI augmentation for architecture governance and intake workflows.

Lead end-to-end delivery of Power Platform and AI-enabled automations using Power Apps, Power Automate, Copilot Studio and PowerShell; support production workloads, perform root cause analysis, maintain runbooks and build Power BI dashboards for platform health and governance.