Top Artificial Intelligence Jobs in Delhi

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 frameworks; developing tests with Python, Java, or Go; integrating testing into CI/CD pipelines; applying AI/ML for test generation and defect analysis; analyzing network and test data; and collaborating with development, product, and QA teams.

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.

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.

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.

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 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.

Build and ship customer-facing AI features for Scout, including agentic LLM workflows, tool calling, RAG pipelines, evaluations, guardrails, and prompt engineering. Develop full-stack services and interfaces using backend languages, TypeScript, React, and mobile technologies. Deploy scalable, secure systems on AWS and Kubernetes, with monitoring, testing, and CI/CD. Own features end-to-end, collaborate with stakeholders, make product decisions, and contribute to reliable AI infrastructure and engineering practices.

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.

Conduct STEM and emerging-technology workshops, demonstrations, presentations, and hands-on learning activities for school audiences. Research innovation trends, develop educational content and programs, demonstrate robotics, AI, ML, and maker-space concepts, and collaborate with internal teams. The role requires strong public speaking, mentoring, communication skills, a personal laptop, bilingual English and Hindi proficiency, and willingness to travel for school visits and workshops.

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.

Manage digital-native customer accounts throughout the sales lifecycle, from pipeline generation and complex deal strategy through deployment and renewal. Own revenue targets and forecasts, develop account plans, analyze account and market intelligence, and advise C-level stakeholders on AI adoption. Collaborate with solutions, engineering, marketing, finance, product, and operations teams to deliver customer programs, influence product strategy, and support team growth.

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.

Design and build reinforcement-learning training environments and diverse tasks to evaluate and improve LLM agents; iterate rapidly on task designs from customer feedback, deliver high-quality outputs with minimal supervision, and maintain PST overlap for collaboration.