Top Artificial Intelligence Jobs in Bengaluru

Build and own backend services, APIs, data models, and algorithmic or AI-driven business logic using Python and Django. Responsibilities include designing relational schemas, implementing RESTful endpoints, optimizing queries and performance, applying caching, translating product ideas into technical designs, and contributing to engineering patterns within a distributed startup team.

Lead development of high-performance, HANA-optimized SAP applications using modern ABAP, CDS Views, AMDP, SQLScript, OData, and APIs. Integrate SAP services with LLMs, RAG, and agentic AI while implementing guardrails, evaluation frameworks, testing, observability, and reliable fallbacks. Collaborate with UX, data, integration, and platform teams to deliver scalable cloud-ready solutions and provide production support.

Lead a technical pod delivering Java full-stack applications with React, Python, AI tools, Spring Boot, microservices, and REST APIs. Provide technical team leadership, guide cloud implementations with a preference for Azure, engage directly with clients, and communicate and present effectively. The role is based in Bangalore or Hyderabad and initially requires five days per week in the office during the general shift.

Develop game concepts by translating requirements into efficient code, producing prototypes, and contributing to design and audio features, while ensuring game polish and maintenance.

Develop games throughout the full lifecycle, translating requirements into efficient code, prototyping gameplay features, contributing to design and audio, resolving technical issues, maintaining code, fixing bugs, and polishing finished products. The role also involves communicating with the team, establishing schedules and milestones, and applying expertise in a specialized area such as AI, 3D rendering, animation, physics, networking, or audio.

Designs and leads enterprise AI Factory and GPU infrastructure architectures spanning compute, networking, storage, Kubernetes, cloud, security, observability, and AI/ML platforms. Assesses workloads, develops reference architectures and detailed designs, performs capacity planning and technology evaluations, leads proof-of-concepts, and supports deployment, migration, troubleshooting, and production transition. Collaborates across infrastructure, security, cloud, data, application, and operations teams to ensure scalable, secure, reliable, and cost-effective AI platforms.

Own the Workato environment, configure enterprise integrations, and build AI-native packages using Workato AI Genie. Design and deploy agent-ready workflows and AI-powered workflow automation solutions, while managing RBAC, auditing, and multi-workspace environments. Integrate Workato with enterprise applications and support scalable workflow implementations.

Build and extend internal operations tools and a customer-facing web app. Integrate business systems through REST APIs, use AI coding tools to prototype and debug, implement access controls, understand data consistency, collaborate directly with users, and document maintainable solutions.

Build and ship full‑stack product features, developer tools, and code‑intelligence workflows using React/Next.js, TypeScript, Node.js/Python, Postgres, and cloud services. Improve AI-assisted developer workflows, create repo‑aware copilots, automate testing/CI checks, review AI-generated code for security and performance, and document reusable patterns and engineering playbooks.

Lead architecture and development of scalable backend and full-stack features for AI-native products, build agentic AI workflows and orchestration, design distributed systems and APIs, ensure security and performance, troubleshoot production, and mentor engineers.

As a Senior Backend Engineer, you will design and maintain scalable software solutions, embrace innovation with AI tools, and ensure high-quality engineering practices.

Build data integrations and tooling that combine CRM, product telemetry, support, billing, and other signals to provide GTM teams with context, automation, and real-time augmentation. Enable account prioritization, allocation, and funnel conversion tracking to increase revenue and save time across sales, marketing, growth, and customer success.

Lead architecture and implementation of scalable, distributed enterprise features across multi-cloud environments. Own full lifecycle from whiteboarding and design to coding, integrations, and post-launch stability. Build agent-driven workflows that connect autonomous AI agents to APIs and data pipelines. Execute as a hands-on individual contributor, leveraging AI tools to accelerate delivery while ensuring secure, observable, and extensible enterprise integrations.

Design and implement AI-enabled ServiceNow solutions across ITSM, FSM, and ITAM. Provide technical leadership and ensure best practices in AI capabilities, facilitate stakeholder workshops, and guide project teams.

Design and presales of end-to-end AI/HPC infrastructure: size GPU clusters, storage, networking, Kubernetes/container platforms, integrate liquid-cooled racks with facility constraints, validate solutions with OEMs, and support delivery for scalable, operable AI deployments.