Top Artificial Intelligence Jobs in Pune

Develops AI- and analytics-driven pre-sales value quantification tools. Responsibilities include managing large datasets with SQL, performing statistical analysis, building Tableau or Power BI dashboards, creating ROI calculators, integrating machine learning, generating strategic insights, and collaborating with Sales, Marketing, Consulting, and Product teams to improve customer engagement and business outcomes.

Own and grow enterprise customer accounts across India by developing territory and strategic account plans, expanding adoption of Atlassian’s SaaS portfolio, and consistently exceeding sales targets. Coordinate with solution engineers, customer success, technical account managers, channel partners, and marketing teams. Build executive relationships, lead consultative solution selling, uncover expansion opportunities, and support cloud migration and business outcomes.

Lead full-cycle recruiting for complex engineering roles across distributed systems, cloud, security, data, and AI/ML in India. Advise engineering leaders on leveling, team design, location strategy, and market intelligence. Build diverse sourcing pipelines, conduct technically credible screens, close senior candidates, improve hiring processes, and lead talent acquisition initiatives. Mentor peers and establish recruiting standards for technical hiring.

Lead the implementation and continuous improvement of an enterprise Project Risk Management operating model and Archer platform. Translate governance, compliance, contractual, and risk requirements into workflows, controls, decision trees, and assessment processes. Drive stakeholder adoption, standardization, governance forums, platform enhancements, and cross-functional collaboration across Legal, Privacy, Security, Compliance, Quality, and Risk teams. Support AI-enabled risk indicators, automation, evidence collection, and decision-support capabilities.

Advise clients on data governance strategies, policies, frameworks, data quality, privacy, security, and metadata management. Execute governance projects, develop thought leadership and accelerators, collaborate with stakeholders, promote data-driven decision-making, and support continuous improvement. The role requires expertise in data governance best practices, privacy regulations, security principles, governance tools, and client-facing consulting.

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.

Leads Financial Crime Technology application development, data architecture, AML and fraud-monitoring technology delivery. Oversees strategy, architecture, budgets, resources, risk, governance, system migrations, and regulatory compliance. Drives AI and generative AI innovation, including machine learning, LLMs, intelligent automation, explainable AI, and responsible-use guardrails. Partners with business, technology, legal, risk, and compliance leaders while managing and developing high-performing teams.

Develop and deploy AI and machine learning solutions for DNV’s maritime business processes. The role covers stakeholder engagement, data analysis, technical architecture, experimentation, programming, testing, DevOps release cycles, and production integration. The successful candidate will identify new applied AI opportunities, collaborate with data scientists, developers, engineers, and domain experts, and contribute to business value through practical AI systems.

Drive enterprise business development by engaging CXO-level stakeholders, building strategic relationships, generating sales pipelines, positioning AI, data, cloud, and hyper-automation solutions, managing end-to-end sales cycles, negotiating agreements, and closing deals. The role requires strong executive communication, networking, analytical thinking, resilience, and technology-sector sales experience.

Design, build, and maintain scalable data pipelines and cloud data platforms to support AI/ML workloads. Deploy, monitor, and operationalize machine learning models, implement CI/CD and MLOps, ensure data quality, scalability, and governance while collaborating with data scientists, engineers, and stakeholders.

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.

Build and deploy AI and machine learning solutions using distributed computing, cloud platforms, data pipelines, and production-grade software engineering practices. Responsibilities include technical requirements analysis, feature development, testing, code reviews, agile collaboration, architecture validation, and prototyping emerging technologies. The role partners with data scientists, architects, client-facing teams, and clients to deliver scalable AI solutions and manage machine learning lifecycles.

Analyze large datasets, investigate data quality and lineage issues, build data pipelines, apply statistical and machine learning techniques, and create dashboards and reports. Translate findings into actionable recommendations for operational improvement, risk mitigation, and strategic decision-making. Partner with business, technology, risk, finance, operations, and data teams while ensuring analytical outputs meet governance, privacy, security, regulatory, and control standards. The role may lead analytical workstreams or teams and influence senior stakeholders.

Supports the design, development, testing, deployment, and maintenance of RPA automations and AI-powered tools under senior guidance. Analyzes business processes, documents requirements and workflows, maintains reusable solution assets, performs basic incident resolution, and contributes to technical reviews and delivery activities. Collaborates with ERP support, software development, and platform engineering teams while building expertise in enterprise automation, AI tooling, development practices, and relevant certifications.

Supports Northern Trust’s enterprise Base Risk Assessment Oversight Program by coordinating assessments, reviewing risk and control information, challenging stakeholders, analyzing trends, maintaining assessment data, and preparing dashboards and executive reporting. The role facilitates risk workshops, supports data quality and calibration activities, contributes to methodology enhancements and remediation, and helps improve risk assessment processes through automation and AI. It requires strong enterprise risk management expertise, analytical ability, communication skills, and stakeholder influence in a regulated financial services environment.

Leads enterprise technology strategy, delivery, and transformation across Finance, FinTech, Legal, and Risk. Oversees product platforms, Agile and DevOps adoption, AI and data initiatives, digital transformation, change management, vendor partnerships, governance, and technology operations. Partners with executive stakeholders to align global priorities, integrate platforms, manage dependencies, and deliver scalable, secure, value-driven outcomes across a federated enterprise technology organization.

Leads the design, implementation, configuration, optimization, and maintenance of Oracle Agile PLM enterprise applications. Manages application access, data integrity, reports, process flows, upgrades, testing, performance, security, issue resolution, and system enhancements. Partners with business, engineering, and IT stakeholders to deliver solutions, improve processes, manage complex problems, and support Agile DevSecOps practices. Mentors team members and coordinates cross-functional initiatives.

Writes high-quality long-form content about AI, enterprise technology, infrastructure, and related topics. Responsibilities include researching complex subjects, developing thought leadership, whitepapers, reports, case studies, website content, and marketing assets; interviewing subject-matter experts; adapting content for varied audiences; editing for accuracy and clarity; and collaborating with marketing and SEO teams.

Build and operate production software and AI systems across cloud infrastructure. Responsibilities include developing APIs and services, operating RAG and inference platforms, implementing CI/CD and observability, managing AWS or GCP environments with Kubernetes and Terraform, optimizing model serving and GPU usage, controlling cloud and AI costs, and partnering with stakeholders on reliability, security, governance, and technical tradeoffs.

Designs, builds, and operates enterprise AI platforms across public and private clouds. Develops MLOps, model deployment, monitoring, observability, governance, automation, and infrastructure capabilities supporting machine learning and generative AI workloads. Responsibilities include troubleshooting production systems, improving reliability and scalability, collaborating with engineering, security, and governance teams, evaluating emerging AI technologies, contributing to architecture and platform strategy, and mentoring peers.

Develop AI-driven products through hands-on software development and product engineering. Build minimum viable products, solve problems creatively, and help shape future AI applications. The role is available remotely or in Boston and Chicago, with contract options ranging from two weeks to three months or full-time, plus potential revenue sharing.

Advises global business teams on privacy, data protection, security, and regulatory compliance. Responsibilities include managing data inventories and mapping, responding to data subject requests and privacy questionnaires, negotiating privacy and security contract terms, conducting impact and risk assessments, supporting incident response, implementing privacy processes and controls, reviewing AI initiatives, assisting with M&A due diligence, and delivering privacy training across the organization.

Lead end-to-end delivery of production-grade ML, Generative AI, and RAG solutions across multiple pods. Develop architecture-aligned delivery plans, manage dependencies, risks, releases, NFRs, and production readiness, while representing teams in senior governance forums. Guide ML versus GenAI decisions, RAG implementation, evaluation, guardrails, security, monitoring, and responsible model usage. Translate technical requirements into actionable epics and stories and ensure measurable business outcomes.

Warriors Lab seeks innovators to develop solutions for real-world problems. Candidates may bring their own idea or join the innovation team to research, design, prototype, build, test, improve, and deliver products. The role offers mentorship, infrastructure, research and testing support, and potential venture leadership. Initial compensation is a small monthly stipend, followed by a full-time fixed salary after successful completion of the first three months.

Build and scale the APAC developer community for an open-source AI foundation. Responsibilities include developer advocacy, contributor programs, technical content, ecosystem partnerships, governance support, events, hackathons, and community metrics. The role serves as a public representative, translates complex technical concepts for developers, and collaborates with maintainers, researchers, enterprises, and open-source communities to grow adoption and participation.