Top Artificial Intelligence Jobs in Bangalore

Develop and maintain scalable Java full-stack software solutions, including technical design, implementation, testing, debugging, architecture reviews, and code reviews. Lead complex technical projects, improve existing systems, support customers, investigate technologies, and mentor developers. The role requires expertise in cloud infrastructure, DevOps, scalable web services, databases, software testing, security, AI modernization, LLMs, and cross-functional technical leadership.

Develop and enhance scalable full-stack enterprise applications using Java and modern frontend frameworks. Build backend and frontend components, integrate REST/GraphQL APIs and AI services, implement RAG features, and use AI-assisted development tools for coding, debugging, testing, and documentation. Collaborate with architects and AI specialists while applying enterprise engineering, SDLC, cloud-native development, and CI/CD best practices. A minimum of 5 years’ experience is stated, with 6 years specifically requested for Java full-stack development.

Develop scalable full-stack enterprise applications using Java and modern frontend frameworks. Build backend and frontend components, integrate APIs and AI services, implement RAG features, and use AI-assisted development tools for coding, testing, debugging, and documentation. Collaborate with architects and AI specialists while applying software engineering, SDLC, agile, quality, and cloud-native best practices.

Develop and enhance scalable Java full-stack software, including highly available web services and distributed systems. Responsibilities include technical design, coding, testing, debugging, code reviews, architecture reviews, system improvements, and technical support. The role also involves cloud infrastructure, CI/CD, DevOps, database integration, security practices, mentoring developers, leading technical initiatives, and translating AI modernization opportunities into business impact.

Develop and enhance scalable enterprise full-stack applications using Java and modern frameworks. Build frontend and backend components, integrate APIs and AI services, implement RAG features, and use AI-assisted development tools for coding, debugging, testing, and documentation. Collaborate with architects and AI specialists while following engineering best practices, SDLC processes, agile methods, cloud-native development, and CI/CD practices. At least 5–6 years of Java full-stack development experience and 15 years of full-time education are required.

Develop scalable full-stack enterprise applications using Java and modern front-end frameworks. Build, integrate, test, debug, and document software components with AI-assisted development tools. Integrate AI services, APIs, and RAG features where relevant while following SDLC, agile, cloud-native, and CI/CD practices. Collaborate with architects and AI specialists to deliver reliable solutions. The role requires at least five years of experience, with six years of Java full-stack development specified, plus 15 years of full-time education.

Develop, maintain, test, and enhance scalable Java full-stack applications and distributed web services. Create technical designs, lead architecture and code reviews, troubleshoot complex systems, and support cloud-based SaaS infrastructure. Collaborate across teams, improve code quality and operational processes, investigate emerging technologies, and mentor developers. The role emphasizes AWS or Azure, DevOps, CI/CD, big data, AI modernization, security, testing, and high-performance systems.

Develop, enhance, test, and support scalable Java full-stack applications and distributed systems. Create technical designs, lead architecture and code reviews, improve existing codebases, and troubleshoot complex issues. Work with cloud infrastructure, DevOps, databases, big data, security, testing, and AI modernization initiatives. Collaborate with cross-functional teams, provide technical guidance, and mentor developers while driving high-quality delivery and independent decision-making.

Develop and enhance scalable Java full-stack software solutions, including web services and distributed systems. Responsibilities include technical design, coding, testing, debugging, code reviews, architecture reviews, documentation, system quality improvements, and technical support. The role leads architecture and implementation efforts, mentors developers, collaborates cross-functionally, and works with cloud infrastructure, CI/CD, big data, AI modernization, and security practices.

Design and scale observability and reliability frameworks using metrics, logs, traces, predictive analytics, anomaly detection, and machine learning. Establish dashboards, SLAs, SLOs, SLIs, and high-availability architecture for distributed systems. Develop AIOps capabilities for root-cause analysis, predictive capacity planning, alert deduplication, and noise reduction. Mentor engineering teams and communicate complex technical concepts to leadership.

Own and scale Azure infrastructure, Azure DevOps CI/CD pipelines, security permissions, and DevOps methodology for Microsoft’s silicon front-end CAD organization. Develop Python-based CAD automation and integrations, improve reliability through monitoring and incident response, partner with EDA, Azure, and security teams, drive infrastructure roadmaps, and mentor engineers and interns.

Engineers, tests, deploys, and maintains secure, scalable software, scripts, and tools across the full development lifecycle. Collaborates with engineers, architects, and business analysts in feature teams, contributing to requirements analysis, design, coding, testing, deployment, operations, automation, optimization, and software engineering best practices.

Lead the design, development, modernization, and maintenance of a cloud-based Studio platform, transitioning it to Java microservices on GCP. Build scalable full-stack features, improve system performance and security, troubleshoot production issues, and use observability tools such as New Relic, Grafana, and Prometheus. Mentor engineers, conduct code reviews, address technical debt, collaborate cross-functionally, and participate in on-call support.

Develop scalable cloud applications and high-quality, secure software. Responsibilities include technical design, coding, debugging, testing, troubleshooting, system optimization, feature delivery, product adoption tracking, and advocating for customer-focused enhancements. The role requires applying software development lifecycle and agile practices, using AI coding assistants to accelerate development, and collaborating with engineering leaders and teams.

Leads platform engineering and AI-enabled operations in a regulated production environment. Responsibilities include hardening and patching operating systems, automating incident response, managing major incidents, improving MTTR, designing infrastructure solutions, enforcing change and compliance standards, and guiding teams through adoption. The role also develops implementation plans, technical documentation, monitoring and recovery standards, and collaborates with architecture, security, development, vendors, and business stakeholders.

Designs, develops, and supports enterprise process automation solutions using PEGA, Automation Anywhere, and Microsoft Power Platform. Leads scalable robotic process automation implementations, Pega workflow and low-code application development, system integrations, and technical design. Collaborates with architecture, engineering, business, and Center of Excellence stakeholders to deliver secure, reusable, sustainable solutions and drive continuous process improvement.

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.

Lead development of observability and data infrastructure for Databricks, building scalable pipelines, integrating with ecosystem tools, optimizing performance and cost, mentoring engineers, and driving cross-functional product milestones from requirements through operation and iteration.

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.

Design, build, and deploy cloud-native full-stack applications on Azure, integrating AI features (search, chat, RAG) across UI, API, services, and data layers. Deliver features end-to-end including tests, code reviews, CI/CD, observability, and security; collaborate with architects and stakeholders and apply Responsible AI principles.

Leads enterprise infrastructure automation and AI Ops across endpoints, identity, Microsoft 365, cloud, networking, and IT service management. Designs policy-as-code, infrastructure-as-code, CI/CD pipelines, API integrations, telemetry, anomaly detection, and secure automated remediation. Owns Intune and Entra ID architecture, Microsoft 365 governance, access lifecycle automation, and AI-assisted operational workflows. Establishes enterprise standards, mentors engineers, and partners across infrastructure, security, identity, network, cloud, and service desk teams.

Design and develop AI SoC logic, including microarchitecture definition, RTL coding, simulation, and IP integration. Optimize designs for power, performance, area, and timing while validating quality, security, and design integrity. Collaborate on verification plans, resolve RTL test failures, perform clock-domain-crossing analysis, and support reliable IP and SoC handoff across the design flow.

The Engineering Specialist is responsible for frontend application development and backend integration, focusing on building scalable web applications, collaborating with teams, and adhering to architecture standards.

Leads enterprise platform architecture, technical governance, cloud-native engineering, automation, and modernization. Designs secure, scalable platforms across AWS, GCP, or multi-cloud environments; builds prototypes and reusable services; remains hands-on with coding; drives Infrastructure as Code, CI/CD, Kubernetes, and platform adoption; mentors engineers and influences stakeholders across the organization.

Designs secure, scalable, resilient Azure enterprise platforms and AI-ready infrastructure. Translates customer requirements into end-to-end architectures spanning networking, identity, security, governance, observability, automation, disaster recovery, and AI workloads. Leads architecture workshops, technical design, implementation guidance, governance, operational readiness, and troubleshooting. Advises customer and engineering stakeholders on cloud and AI adoption roadmaps, technical trade-offs, risks, costs, and responsible AI controls.