Sr. Gen AI Engineer
Jobgether
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This role on the market
102 open gen roles across 37 companies are on ApplySarthi right now, most of them in Bengaluru (10), Hyderabad (5), Delhi NCR (5).
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What gen roles keep asking for: Python (37%), Generative AI (36%), LLMs (28%), AWS (26%), RAG (25%), CI/CD (20%), Docker (20%), Azure (19%) — counted across their open postings here.
CI/CD jobs · Docker jobs · Generative AI jobs · Kubernetes jobs
Jobgether has 4,275 open roles listed here.
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Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for gen roles keep coming back to Python, Generative AI, LLMs, AWS. Practise those questions before you sit with Jobgether.
Questions you are likely to be asked
- Why do you want to join Jobgether?
- What is your experience with LLMs? Tell me one thing you learned the hard way.
- How would you explain your model's result to someone who is not technical?
- What would you check first if a model's accuracy dropped after going live?
- When would you not use machine learning for a problem?
Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.
Practise the Sr. Gen AI Engineer at Jobgether interview free →Accountabilities: Design, develop, and implement scalable AI and Generative AI solutions aligned with business and product requirements. Build and productionize LLM-powered applications, intelligent automation systems, and AI-driven workflows. Partner directly with customers, product teams, and internal stakeholders to understand real-world challenges and deliver tailored AI solutions. Translate ambiguous business requirements into practical AI architectures, prototypes, and production-ready implementations. Develop, test, deploy, and optimize AI models and applications across cloud and enterprise environments. Integrate foundation models and LLM APIs into scalable applications while considering performance, reliability, security, and cost. Evaluate emerging Generative AI technologies, frameworks, and models and assess their suitability for specific business use cases. Troubleshoot model and application issues while continuously improving quality, latency, scalability, and accuracy. Collaborate with software engineers, data scientists, product managers, and other stakeholders to deliver end-to-end AI solutions. Develop reusable components, APIs, tools, and frameworks that accelerate the deployment and adoption of AI applications. Establish effective evaluation, monitoring, testing, and observability practices for AI and LLM-based systems. Stay current with developments in Generative AI, LLMs, AI agents, model orchestration, and enterprise AI deployment. Requirements 5–13 years of professional experience in software engineering, Artificial Intelligence, Machine Learning, or related technical fields. Strong hands-on experience developing AI and Generative AI applications. Solid understanding of Large Language Models, foundation models, prompt engineering, model APIs, and AI application architecture. Proven ability to take AI solutions from experimentation and prototyping through production deployment. Strong forward deployment engineering mindset, with the ability to work directly with users or customers and rapidly develop solutions around their requirements. Strong programming fundamentals and software engineering expertise. Experience designing scalable, reliable, secure, and maintainable AI-powered systems. Ability to independently investigate technical problems, navigate ambiguity, and deliver solutions in rapidly changing environments. Strong communication and collaboration skills, particularly when working with both technical and non-technical stakeholders. Experience with LangChain or comparable LLM orchestration frameworks is advantageous. Hands-on experience building Agentic AI systems, autonomous workflows, or AI agents is a plus. Experience implementing Retrieval-Augmented Generation (RAG), vector databases, embeddings, semantic search, and document-processing pipelines is desirable. Familiarity with AI evaluation frameworks, observability, guardrails, and LLM application monitoring is beneficial. Experience with cloud platforms and modern deployment practices such as Docker, Kubernetes, and CI/CD is preferred. Exposure to multi-agent architectures, tool calling, function calling, and workflow orchestration is an advantage. Benefits Freelance / contract engagement. Remote working opportunity within India. Compensation range of ₹10,00,000–₹65,00,000 per year , as stated in the original posting. Opportunity to work on advanced AI and Generative AI initiatives. Exposure to LLMs, AI agents, RAG, model orchestration, and emerging AI technologies. Direct collaboration with customers, product teams, software engineers, and other technical stakeholders. Opportunity to work on AI solutions from early experimentation through production deployment. Flexible environment suited to experienced engineers who value autonomy and ownership.
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Listed on lever · posted 2026-10-02. ApplySarthi collects openings and links to application pages; the role is advertised by Jobgether, not by us.