Top Artificial Intelligence Jobs in Bengaluru

Develop and support SAP frontend solutions using HTML, CSS, JavaScript and SAP UI5. Work on S/4HANA transformation tooling integrating AI for automated test case, data, and script generation. Participate from backlog validation through realization, collaborate across SAP teams, identify risks, and deliver to specifications.

Develop and optimize astrodynamics algorithms for space situational awareness, including orbit determination, propagation, conjunction analysis, and orbital prediction. Improve scalable, production-grade software and support system integration, testing, deployment, and operations. Research advanced numerical, AI, machine learning, and cloud-based techniques; collaborate across engineering, data science, operations, and product teams; mentor junior staff; and contribute to technical documentation, proposals, publications, and intellectual property.

Lead development and optimization of astrodynamics algorithms for orbit determination, propagation, conjunction analysis, and prediction. Design, validate, and operationalize scalable, efficient SSA software; research ML/AI and numerical methods; mentor junior engineers; collaborate across software, data science, operations, and product teams; contribute to documentation, proposals, and publications.

Own end-to-end quality for web platforms and mobile apps by writing test cases, building automated regression suites, evaluating AI-powered testing tools, validating data and user journeys, and supporting releases. The role includes bug reporting, production investigation, customer-facing technical support, documentation, and collaboration with engineers to verify fixes. The engineer will work with Playwright, Cypress, Selenium, and AI tools while developing broader engineering skills.

Build and operate an AI-first developer platform, including CI/CD pipelines, Kubernetes-based tooling, developer products, and autonomous agents for remediation, upgrades, scanner triage, and credential rotation. Establish secure agent controls, observability, infrastructure as code, and zero-downtime practices. Run measurable experiments, improve DORA performance, collaborate with delivery teams, and influence the platform roadmap in a regulated environment.

Build and operate scalable Java backend services and APIs supporting AI-powered and traditional product capabilities. Integrate LLMs, agents, and retrieval systems into production applications while improving evaluation, monitoring, observability, CI/CD, security, reliability, and performance. The role requires collaboration with AI Engineers, Product Owners, and Cloud Operations teams in a hybrid Bangalore environment.

Develop and maintain custom ERPNext and Frappe applications, including DocTypes, workflows, reports, dashboards, print formats, integrations, and APIs. Diagnose bugs, improve performance, maintain existing customizations, and manage deployments through Git and staging environments. Use and review AI-generated code for implementation, debugging, testing, refactoring, security, and maintainability. Communicate progress and clarify requirements while supporting ERPNext workflows and related infrastructure.

Designs and maintains large-scale, multi-module Android applications using Kotlin, Jetpack Compose, Gradle, and scalable architecture. Responsibilities include optimizing builds and app performance, diagnosing memory issues and ANRs, implementing dependency injection and automated testing, and analyzing Firebase Crashlytics data. The engineer also integrates LLM APIs, MCP frameworks, token and context management, agentic workflows, multi-agent orchestration, and AI recovery strategies into production mobile applications while collaborating across engineering, product, QA, and architecture teams.

Own architecture for high-scale Android applications, build Gradle and Jetpack Compose solutions, integrate LLM and MCP capabilities, resolve performance issues, and maintain testable MVVM/Clean Architecture code. Lead applications through the full lifecycle, including CI/CD and Google Play releases, while influencing multiple teams and communicating technical tradeoffs to senior stakeholders.

Leads the architecture and delivery of a customer-facing SDK for an edge AI SoC. Owns APIs, command-line tools, samples, documentation, developer workflows, packaging, compatibility, release readiness, and developer portal requirements. Partners across AI, multimedia, robotics, kernel, tools, and SQA teams to support board bring-up, model deployment, camera pipelines, ROS examples, and production workloads. Hires, mentors, and leads engineers focused on SDKs, developer tools, documentation, portals, and sample applications.

Develop and maintain enterprise-grade Java full-stack applications using Spring Boot and modern frontend frameworks. Integrate AI capabilities, particularly RAG architectures, into cloud-native solutions. Build REST and GraphQL APIs, manage SQL and NoSQL databases, deploy cloud solutions, and maintain CI/CD pipelines. Collaborate across teams, conduct code reviews, mentor developers, and apply Java, C#/.NET, frontend, cloud, and AI expertise to deliver scalable software.

Design and maintain automated testing frameworks using Playwright and Selenium, including functional, regression, and API testing. Test SAP BTP applications and integrations, apply AI and LLM techniques to improve test generation and execution, and manage defects through resolution. The role also performs manual exploratory testing, develops test strategies, and collaborates with cross-functional teams to support reliable, high-quality software releases.

Develop cloud-native enterprise applications with SAP ABAP Cloud and SAP BTP while adhering to Clean Core principles. Design secure authorization frameworks, enterprise APIs, and event-driven architectures. Integrate LLMs, AI services, and Agent Frameworks for orchestration and automation. Implement vector databases and semantic search capabilities to improve intelligent data retrieval. Build scalable, resilient solutions with strong enterprise security and system integration.

Leads enterprise architecture for cloud-native Java applications across multiple product domains. Defines architecture standards, microservices, APIs, data strategies, observability, testing, CI/CD, and Kubernetes-based GCP deployments. Drives AI-augmented development, including LLM integrations, RAG, vector stores, and internal productivity tools. Mentors engineers, conducts architecture reviews, evaluates technologies, and aligns technical roadmaps with business objectives.

Test a rules-to-proof AI product across rule inputs, formal specifications, prover outputs, proof artifacts, APIs, and proof viewers. Identify functional defects, edge cases, security risks, malformed inputs, conflicting rules, and data-handling issues. Create reproducible bug reports, verify fixes, and progressively automate testing using Python, pytest or similar frameworks, and CI/CD tools.

Build and operate production backend services supporting Supabase AI products, including the MCP server. Responsibilities include service architecture, deployments, scaling, authentication and authorization, observability, reliability targets, on-call incident response, rate limiting, capacity management, and API evolution. The role requires strong TypeScript or Go skills, production backend experience, distributed-systems debugging, and collaboration with Platform and SRE teams in a fully remote environment.

Leads AI-assisted software delivery while combining business analysis, Scrum Master responsibilities, and hands-on technical leadership. Translates business needs into requirements, user stories, technical designs, and production solutions. Facilitates Agile ceremonies, manages dependencies, mentors developers, reviews code, and contributes to APIs, integrations, UI components, testing, CI/CD, and deployment automation. Ensures secure, responsible AI use, traceability, production readiness, stakeholder alignment, and measurable delivery improvements.

Design, implement, review, and validate production-grade Rust backend systems for AI training projects. Responsibilities include API development, persistence, asynchronous processing, concurrency, performance optimization, reliability testing, architecture assessment, debugging, and creating reproducible environments with databases, dependencies, fixtures, and containers. The role requires clear technical documentation, evaluation of failure scenarios and race conditions, and consistent delivery of high-quality implementation artifacts.

Own verification of custom AI accelerator hardware, including matrix and vector compute engines. Develop SystemVerilog and UVM environments, reference models, assertions, checkers, coverage, and regression infrastructure. Verify numerical precision, quantization, data flow, performance, and reliability across RTL blocks and subsystems. Collaborate with architecture, RTL, software, compiler, and runtime teams through emulation and silicon bring-up.

Build and maintain scalable, low-latency backend systems for real-time AI and voice workflows. Responsibilities include developing microservices, APIs, streaming systems, concurrent and fault-tolerant code, observability, testing, deployment, and monitoring. The role integrates WebRTC and telephony protocols, Voice AI, LLMs, vector databases, and agent frameworks while collaborating with product, AI, and ML teams on multi-agent orchestration and automation.

Build and maintain full-stack web and mobile applications, campaign and influencer marketing tools, dashboards, workflow automations, AI-driven tools, and third-party API integrations. Develop with React, Node.js, and Python; manage deployments, CI/CD, monitoring, and basic infrastructure. Own projects end to end, guide junior developers, conduct code reviews, and collaborate with founders, marketers, and nontechnical teams.

Conduct online robotics and STEM classes for students aged 8–16, teaching Arduino, IoT, electronics, sensors, automation, coding, and AI basics. Mentor students through robotics projects, innovation challenges, competitions, and presentations. Create engaging virtual learning experiences, troubleshoot project and coding issues, and support Indian and international students.

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.

Build and ship end-to-end product features across React frontends and Django backends. Design data models, RESTful APIs, responsive user interfaces, and algorithmic or AI-driven logic involving scoring, ranking, and decision rules. Optimize performance through efficient queries and caching, write production-ready code, and work independently with a distributed startup team. Experience with GCP, Redis, Docker, Kubernetes, React Native, or AI coding assistants is advantageous.

Lead cloud and platform architecture for scalable AI and SaaS systems. Design AWS multi-region infrastructure, HA/DR environments, Kubernetes clusters, networking, storage, and Infrastructure-as-Code. Bridge application engineering and infrastructure by reviewing architectures, improving backend performance, building platform tooling, mentoring engineers, and enabling cloud-native reliability. Own observability, incident response, root-cause analysis, and deployment automation while supporting security scanning and compliance alignment.