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Gartner

Sells research and advice to business leaders

Lead Software Engineer-Gen AI - NLP, ML

AI Application EngineeringUpdated on Nov 9
Full-timeChennai, Tamil Nadu, IndiaNo salary listedIn-person

About the Job

Requirements

  • 6–8 years of professional experience in applied AI/ML, data science, machine learning, algorithms, statistics, or a related technical field, including hands-on experience developing and evaluating AI solutions using natural language processing, deep learning, large language models, retrieval, and agentic AI.
  • A bachelor's or master's degree in Engineering, Data Science, Computer Science, or a related field is required.
  • Hands-on experience developing and evaluating machine learning and natural language processing solutions, including transformer architectures, deep learning, embeddings, information retrieval, classification, ranking, summarization, question answering, and agent decision-making.
  • Experience working with large language models and foundation models such as OpenAI, Anthropic, Cohere, Llama, or equivalent technologies.
  • Experience building generative AI and agentic AI solutions using technologies such as LangChain, LangGraph, retrieval-augmented generation, prompt engineering, model context protocol, or equivalent frameworks.
  • Experience evaluating large language model and agent performance across accuracy, relevance, groundedness, helpfulness, safety, latency, and cost.
  • Experience designing AI-focused guardrails and applying responsible AI practices, including hallucination mitigation, output validation, policy adherence, and human oversight.
  • Ability to identify emerging AI technologies and apply them to meaningful business use cases.
  • Ability to explain complex technical concepts to technical and non-technical stakeholders.
  • Ability to collaborate with product, data science, engineering, cloud, security, and platform teams.
  • Comfort working through ambiguity and delivering solutions through short, iterative Agile development cycles.

Responsibilities

  • Design and develop algorithms and AI solutions using large language models, natural language processing, deep learning, generative AI, information retrieval, and feedback-based techniques for agentic AI, knowledge retrieval, summarization, retrieval-augmented generation, and related applications.
  • Design agent architectures, including planning, tool use, memory, orchestration, multi-step reasoning, feedback loops, and execution control.
  • Develop data-processing and representation techniques that transform unstructured text and other data into structured formats for modeling, retrieval, and analysis.
  • Build evaluation frameworks and benchmarks to assess large language model and agent performance across accuracy, relevance, groundedness, helpfulness, safety, latency, and cost.
  • Optimize model performance through prompt engineering, retrieval optimization, reranking, embedding techniques, model selection, and fine-tuning.
  • Design AI-focused guardrails and mitigation approaches, including input and output validation, hallucination mitigation, policy adherence, responsible AI practices, and human-in-the-loop review, in collaboration with security and platform teams.
  • Apply natural language processing, machine learning, statistical analysis, and information retrieval techniques to identify patterns, relationships, and insights in complex data.
  • Translate business requirements into applied AI approaches, algorithm designs, experiments, and measurable outcomes.
  • Stay current with emerging large language model architectures, foundation models, agent frameworks, retrieval techniques, and AI research.
  • Lead technical discussions and mentor team members on algorithms, modeling approaches, experimentation, and AI best practices.

About the Company

Gartner

Sells research and advice to business leaders

Gartner sells business and technology research to executives and their teams, along with advice for decisions about strategy, spending, and operations. Clients use its reports, benchmarking tools, and conversations with experts to evaluate vendors, compare practices, and plan investments. Its consulting teams work on technology strategy and complex projects, while conferences bring leaders together for expert sessions and peer discussions. The company earns revenue from research subscriptions, consulting engagements, and conference attendance, serving organizations across many sectors. Gartner was founded in 1979 and is headquartered in Stamford, Connecticut.

Company size
10,001+
Company stage
IPO
Headquarters
Stamford, CT
Founded
1979

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