Top Artificial Intelligence Jobs in Pune

Implement and customize ServiceNow ITSM and Service Portal solutions, perform integrations (REST, SOAP, MID Server), maintain Discovery and CMDB, develop and optimize server/client scripts (Business Rules, Script Includes, UI Policies), run workshops/demos, translate client requirements into user stories, mentor junior developers, and participate in Agile delivery cycles.

Lead design, customize, and implement ServiceNow ITSM, Service Portal, and ITOM solutions. Perform integrations (REST, SOAP, MID Server), Discovery and CMDB maintenance, and develop/optimize scripts. Run workshops, mentor junior developers, and participate in Agile delivery to translate client requirements into scalable ServiceNow solutions.

Design, scale, and maintain Salesforce Flow and orchestration workflows to automate seller, recruiter, and ops tasks. Implement Agentforce and AI-driven next-best-action processes, build repeatable automation frameworks across service lines, identify data quality gaps, create SLA triggers/escalations, run experiments, and maintain documentation and governance.

Own enterprise customer success from onboarding through ongoing account growth while designing, testing, and refining prompts for multilingual voice and chat AI agents. Define and analyze performance KPIs, identify conversation and workflow improvements, lead training and go-live support, translate client needs into product requirements, and collaborate with engineering and product teams to improve agent outcomes, adoption, retention, and ROI across BFSI use cases.

A six-month, unpaid remote fellowship focused on AI-assisted growth marketing. Fellows develop brand strategy, create Instagram visuals and video assets, learn content repurposing, analyze performance with Google Analytics 4, apply SEO basics, and execute distribution strategies. Participants work asynchronously through SOPs and monthly capstones, producing six case studies, a final exit report, and a competency certification upon successful completion.

Develop, fine-tune, deploy, and optimize AI/ML models and LLM-based RAG systems using Python, AWS Bedrock, and major ML frameworks. Build scalable REST APIs and microservices with FastAPI or Flask, deploy containerized solutions on AWS, and manage CI/CD. Design databases and automated ETL pipelines, integrate cloud services, and document AI workflows while collaborating with cross-functional technical and product teams.

Build and deploy internal AI agents, workflow automations, RAG systems, tool integrations, and copilot experiences across support, sales, recruiting, customer success, and engineering. Responsibilities include designing multi-step agent workflows, integrating Slack, Jira, CRM, email, and other systems, implementing access controls, adding observability and guardrails, and documenting runbooks. The role requires rapid delivery of production-ready MVPs and reusable connectors.

Implement, configure, and support Oracle Fusion Procurement modules and related SCM processes. Gather requirements, design solutions, configure workflows and procurement controls, support AI-driven automation, manage integrations and data migration, conduct testing and UAT, resolve defects, prepare documentation, train users, and provide production support. Collaborate with Finance, Accounts Payable, Inventory, Supplier Portal, and other stakeholders while assessing quarterly Oracle releases.

Develop and optimize machine learning models for production, collaborate with research and engineering teams to integrate AI solutions, research emerging AI methods, participate in code reviews, and contribute to technical documentation. The six-month remote or hybrid internship includes expert mentorship, flexible hours, a completion certificate, and a tool allowance.

Design, develop, deploy, and maintain AI and machine learning solutions. Responsibilities include building models, using LLMs to create and optimize challenge datasets, training and evaluating models, integrating AI into production systems and APIs, conducting research, monitoring performance, and maintaining scalable documentation and code. The role collaborates with data scientists, software engineers, and product teams.

Create and optimize AI prompts for cinematic image and video generation in a theatrical feature film. Translate directors’ vision into high-quality visuals using cinematography, framing, lighting, and storytelling principles. Collaborate with directors, editors, and creative teams to maintain visual consistency, continuity, and coherence across scenes. Experiment with AI generation tools, troubleshoot outputs, and refine results to meet professional film-quality standards.

Support enterprise AI transformation PMO by enforcing governance, producing executive reports and dashboards, managing RAID logs, coordinating cross-platform planning and delivery, driving risk escalation and mitigation, and enabling stakeholder communications and continuous improvement of operating model and playbooks.

Lead design, build, and scale production-grade Generative AI applications using LLMs, RAG, LangChain, vector databases, and agentic systems. Own AI orchestration, containerized Kubernetes deployments, CI/CD, data ingestion from enterprise sources, monitoring for high uptime, and governance/compliance to deliver measurable business impact and reusable AI accelerators.

Own product areas in BJAK's AI Neobank app (insurance, payments, savings, investing, travel). Define problems, scope, success metrics and roadmaps; collaborate with engineering, design, data, ops, compliance and business teams; launch features, monitor performance, run experiments and iterate to improve user experience and business impact.

Lead product direction and roadmaps for major areas of BJAK's AI neobank app. Own prioritization, execution, launch quality, and metrics across multiple squads. Guide PMs, designers, and engineers, turning regulatory and operational constraints into practical product decisions across payments, savings, investing, insurance and travel.

Design and optimize on-device AI inference stacks for RTX and DGX systems: develop inference runtimes, optimize models and pipelines for low-latency/efficient memory use, perform system-level debugging and performance-accuracy analysis, and collaborate across software, research, and product teams to productionize local AI workloads.

Build and productionize LLM-powered agents, workflows, and RAG systems. Apply prompt engineering, embeddings, fine-tuning, and traditional ML to automate tasks and improve products. Mentor teammates and help design scalable, production-grade AI infrastructure while staying current on LLM advances.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, TensorFlow) and integrate LLM APIs. Collaborate with stakeholders, troubleshoot and document workflows, and stay current on generative AI and automation technologies.

Design, build, and optimize AI-driven automation workflows using platforms like n8n, Make, and Zapier. Train, fine-tune, and deploy custom LLMs (OpenAI, Hugging Face, etc.), integrate LLM APIs, collaborate with stakeholders, troubleshoot and document solutions, and stay current on generative AI advances. Mandatory technical assessment required.

Embed with customers to understand their technical environments, build and deploy custom integrations and workflows, write production code, prototype and scale solutions, debug complex issues, and translate customer insights into product requirements. Partner with sales and customer success on technical evaluations, pilots, and POCs while identifying broader platform opportunities. The role requires customer travel of approximately 20–50%.

Build end-to-end infrastructure for AI agents: design React/TypeScript UIs, implement Python agent harnesses, develop Kubeflow-based MLOps pipelines, fine-tune foundation LLMs (LoRA/QLoRA/SFT/RLHF), deploy and operate services on Kubernetes, integrate agent frameworks, and apply software engineering best practices, testing, and CI/CD.

Design and implement production-grade AI agent harnesses, build and operate MLOps pipelines with Kubeflow, fine-tune foundation LLMs (LoRA/QLoRA, SFT, RLHF), deploy and manage services on Kubernetes, integrate agent frameworks, and apply software engineering best practices to move models from prototype to production.

The AI Creative Designer creates high-quality, AI-generated visuals for marketing campaigns, collaborating with teams to optimize visual content for conversion rates.

Evaluate and improve AI-generated tax analyses by reviewing legal and tax documentation, analyzing statutory language, identifying compliance issues, contributing to tax AI datasets, and providing structured feedback while monitoring U.S. tax law updates.

Contractor role to review and analyze U.S. tax statutes, Treasury Regulations, and the IRC; interpret complex tax provisions and identify nuances; summarize tax concepts into structured insights; provide feedback to improve AI-generated tax responses; and collaborate with AI development teams while staying current on legislative changes.