Top Artificial Intelligence Jobs in Pune

Designs and develops scalable automated testing solutions for carrier-grade, cloud-native network products. Responsibilities include building functional, regression, performance, and end-to-end test suites; integrating testing into CI/CD pipelines; applying AI/ML for test generation, anomaly detection, defect prediction, and self-healing automation; analyzing network and test data; and collaborating with development, product, and QA teams.

Own the Salesforce platform and broader integration architecture end to end. Design data models, integrations, automations, custom Apex and LWC solutions, deployments, CI/CD pipelines, and Git-based change control. Apply AI-assisted development using Claude and related tools with rigorous review, testing, and controlled releases. Lead technical delivery for developers and QA testers, manage sprint flow and debugging, translate business requirements into technical solutions, and establish platform engineering standards across the technology ecosystem.

Maintain and optimize production LLM and VLM services, including Flask/FastAPI microservices, Dramatiq queues, REST APIs, and Uvicorn/Gunicorn deployments. Design prompt strategies, feedback and evaluation pipelines, and AI routing integrations while monitoring latency, token usage, quality, and errors. Collaborate with engineering teams on scalable microservices, Dockerized deployments, CI/CD, security, and cloud infrastructure.

Leads end-to-end development of enterprise AI and LLM applications, including architecture, technical design, Java and Spring Boot backend development, integrations, testing, deployment, and support. Builds generative AI solutions using major LLM providers, prompt engineering, fine-tuning, and agent frameworks. Collaborates with architects and developers to translate designs into scalable microservices, while addressing security, resiliency, databases, containers, Kubernetes, and cloud platforms.

Lead and mentor 5–10 technical trainers creating and evaluating terminal-based AI training tasks. Review software, computational, electrical engineering, circuit, HDL, simulation, and automated grading tasks for correctness, reproducibility, numerical accuracy, performance, and reliability. Identify flawed assumptions, nondeterminism, race conditions, testing weaknesses, and technical inaccuracies. Allocate work, resolve blockers, provide detailed feedback, track revisions, and maintain technical documentation and quality standards.

Leads technical planning, requirements gathering, estimation, architecture, development, testing, deployment, documentation, and support for client applications. Mentors developers, provides technical leadership, collaborates with solution architects, translates designs into technical requirements, manages projects, and communicates with technical and non-technical stakeholders in a consulting environment.

Lead technical consultant responsible for the full software development lifecycle, including technical design, implementation, testing, deployment, documentation, and support. Builds enterprise AI and LLM applications using OpenAI, Anthropic, Gemini, agent frameworks, Java, Spring Boot, Python, microservices, databases, containers, Kubernetes, and cloud platforms. Collaborates with architects and developers to translate designs into technical solutions while ensuring security, resiliency, and enterprise architecture standards.

Lead technical consultant responsible for designing, developing, testing, deploying, documenting, and supporting enterprise applications. The role focuses on generative AI and LLM integrations using OpenAI, Anthropic, Gemini, prompt engineering, fine-tuning, and agent frameworks. Responsibilities also include Java and Spring Boot backend development, Python, Oracle, microservices, Docker, Kubernetes, cloud platforms, security, resiliency, and enterprise architecture. Requires 8+ years of software development experience and strong AI/LLM application expertise.

Lead technical consultant responsible for designing, developing, testing, deploying, documenting, and supporting enterprise applications. The role focuses on generative AI and LLM integrations using OpenAI, Anthropic, Gemini, agent frameworks, Java, Spring Boot, Python, microservices, databases, containers, Kubernetes, and cloud platforms. The consultant collaborates with architects and developers to translate designs into technical solutions and provides expertise in security, resiliency, and enterprise architecture.

Uses AI tools, digital platforms, LinkedIn, job portals, ATS systems, and online sourcing methods to identify executive-level opportunities across the UAE and GCC. Responsibilities include tailoring applications, researching employers, connecting with recruiters, tracking applications and follow-ups, and improving recruitment workflows through automation. Requires at least three years of talent acquisition or sourcing experience, strong AI tool proficiency, excellent written English, attention to detail, and independent execution.

Own the strategy and roadmap for Netomi’s enterprise AI Agents platform. Partner with customers, engineering, research, data science, and go-to-market teams to prioritize and ship capabilities. Build agent prototypes, connect APIs and MCP tools, design evaluations, analyze model quality, debug production failures, and establish governance, observability, and rollout practices. Drive measurable outcomes including resolution rate, cost, CSAT, adoption, and revenue expansion.

Design and build scalable Playwright and TypeScript UI/API automation frameworks, integrate testing into CI/CD, reduce flakiness, troubleshoot failures, and establish automation architecture and quality metrics. Apply Agentic AI, LLM evaluation, RAG testing, self-healing automation, and intelligent test analysis. Collaborate with engineering and product teams, contribute to test strategy and architecture reviews, mentor engineers, and develop reusable automation tools and AI-enabled quality engineering solutions.

Lead capture and translation of business requirements for Salesforce Sales Cloud and Experience Cloud. Partner with business leaders to define system goals, prioritize scope, drive implementations, and produce functional and technical designs for engineering teams. Support CRM evolution, agile delivery, and top-of-funnel processes like lead, account, and partner management.

Build data infrastructure and reliable pipelines, analyze product usage, train traditional and LLM-based models, define product metrics, run experiments, and translate findings into product and go-to-market decisions. The role combines data science, data engineering, product analytics, machine learning, and stakeholder communication, with ownership across data modeling, evaluation, experimentation, and product insight generation.

Design, build, and deploy production generative AI features, including LLM applications, RAG pipelines, and agentic systems. Develop scalable Python and cloud backend services, evaluate model accuracy and performance, optimize reliability and cost, and implement monitoring, security, and observability. Collaborate with product, design, and engineering teams while mentoring teammates and exploring emerging AI technologies.

Develop, deploy, and maintain scalable AI/ML pipelines and production systems, including LLMs and generative AI models. Collaborate with data scientists, software engineers, architects, and clients to integrate AI capabilities into products. Optimize model performance, latency, and cost on AWS, GCP, and Azure, using Docker, Kubernetes, CI/CD, monitoring, versioning, and other MLOps practices.

Lead and scale an AI-driven creative design team producing performance marketing assets for paid media. Own creative direction, production workflows, quality control, testing, and performance-driven iteration. Develop AI tool expertise, prompt and style libraries, and automated workflows with engineering partners. Collaborate with marketers, media buyers, copywriters, producers, and video editors while remaining hands-on with design and AI tools.

Build and deploy production AI systems, agents, APIs, backend services, data pipelines, and models. Work directly with customers to translate business challenges into technical solutions, automate workflows, run experiments, measure outcomes, and iterate quickly. The role requires strong software engineering and system design fundamentals, AI knowledge, cloud or Kubernetes familiarity, comfort with ambiguity, and strong communication skills.

Lead the vision, strategy, and execution of HighLevel’s Email AI platform. Responsibilities include generative email content and layout creation, autonomous lifecycle sequence generation, predictive send optimization, AI governance, privacy safeguards, roadmap development, instrumentation, and cross-functional alignment. The role aims to accelerate campaign creation, improve engagement, and launch Email AI and Sequence AI capabilities at scale.

Design and build production AI-powered analytics: conversational interfaces, LLM agents, semantic data models, and scalable data pipelines. Partner with Product and Engineering to deploy RAG/MCP-based solutions, integrate AI with enterprise data and cloud platforms, mentor teams, and promote Responsible AI practices to improve decision-making and automation across the company.

Design and develop scalable, resilient cloud architecture integrated with on-premises systems. Drive technical direction, identify platform efficiency opportunities, communicate complex architecture, and implement changes that improve reliability and supportability. Own critical software projects through design, implementation, quality assurance, deployment, and monitoring while providing technical leadership to engineers.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Own and operate a production agentic AI platform while building full-stack features across React and FastAPI. Manage AI workflows, prompts, guardrails, human-in-the-loop approvals, evaluations, bias governance, and RAG knowledge bases. Maintain enterprise and recruiting-channel integrations, MongoDB/DocumentDB pipelines, AWS infrastructure, CI/CD, observability, security, auditability, and PII protection. Partner with HR, recruiting, legal, compliance, and IT stakeholders while leading platform knowledge transfer and roadmap delivery.

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.

Design, develop and deliver enterprise-scale AI/LLM solutions and agents using Python and orchestration tools. Collaborate cross-functionally, enforce secure coding and unit testing, lead or coach teams, and drive technical decisions and risk controls.