PUNE · FULLTIME
AI Engineer
Umanist NA
Pune · onsite · Posted 30d ago
Sourced from
Not disclosed4–8 yrsfulltimePune
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Section · 01
About this role
Location: Pune, Maharashtra
Work Mode: Hybrid
Experience: 4–8 Years
Notice Period: Immediate to 45 Days(525)
Role Summary
We are looking for an experienced AI Engineer to design, develop, and scale production-grade AI and Generative AI applications.
The role involves building LLM-powered applications, RAG pipelines, agentic systems, automation workflows, APIs, and enterprise integrations. The ideal candidate should have strong software engineering fundamentals, hands-on AI/GenAI experience, and excellent communication skills.
Key Responsibilities
2 Technical Rounds → 1 Client Round → HR Round
Keywords
AI Engineer | Generative AI | GenAI | LLM | Large Language Models | RAG | AI Agents | Python | TypeScript | Machine Learning | APIs | Microservices | Kubernetes | Docker | CI/CD | AWS | Azure | GCP | Vector Database | Hybrid Search
Skills: advanced retrieval techniques,kubernetes,ai/ml frameworks,vector databases,hybrid search,apis,distributed systems,ai roles,azure,typescript,rag pipelines,aws,artificial intelligence strategy,software engineering,python,microservices,llms,ci/cd pipelines,agentic ai,docker,devops
Work Mode: Hybrid
Experience: 4–8 Years
Notice Period: Immediate to 45 Days(525)
Role Summary
We are looking for an experienced AI Engineer to design, develop, and scale production-grade AI and Generative AI applications.
The role involves building LLM-powered applications, RAG pipelines, agentic systems, automation workflows, APIs, and enterprise integrations. The ideal candidate should have strong software engineering fundamentals, hands-on AI/GenAI experience, and excellent communication skills.
Key Responsibilities
- Design, develop, and deploy end-to-end AI and GenAI applications.
- Build and integrate LLM-powered applications, RAG pipelines, AI agents, and automation workflows.
- Develop scalable APIs and microservices for AI solutions.
- Design and implement robust data pipelines and retrieval systems.
- Work on prompt engineering, model evaluation, and performance optimization.
- Build reliable and scalable AI services suitable for production environments.
- Implement observability, monitoring, and reliability practices for AI applications.
- Work with distributed systems and cloud-based architectures.
- Collaborate with technical and business stakeholders to develop AI-driven solutions.
- Contribute to system design, engineering best practices, and technical documentation.
- Mentor junior engineers and support knowledge-sharing initiatives.
- 4–8 years of experience in software engineering and/or AI roles.
- Strong hands-on programming experience in Python or TypeScript.
- Practical experience working with Large Language Models (LLMs).
- Hands-on experience building RAG pipelines.
- Experience with AI/ML frameworks and libraries.
- Strong understanding of Artificial Intelligence and Machine Learning concepts.
- Experience building and integrating APIs and microservices.
- Experience working with distributed systems.
- Familiarity with Kubernetes and Docker.
- Experience with CI/CD pipelines and DevOps practices.
- Hands-on experience with at least one cloud platform: AWS, Azure, or GCP.
- Excellent verbal and written communication skills.
- Strong problem-solving and collaboration skills.
- Experience with agentic AI and agent frameworks such as:
- LangGraph
- Semantic Kernel
- Knowledge of vector databases.
- Understanding of hybrid search and advanced retrieval techniques.
- Strong knowledge of system design, scalability, and performance tuning.
- Experience with enterprise system integrations, such as:
- CRM
- ERP
- ITSM
- Experience designing production-grade AI platforms and services.
- Knowledge of AI application observability, evaluation, and monitoring.
- Candidates should have minimum 2 years of stability in an organization.
- Immediate to 45 days notice period preferred.
- Local Pune candidates are preferred
- Temporary accommodation may be provided for a couple of weeks.
- Excellent communication skills are essential as this is a client-facing role involving regular interaction with stakeholders and teams.
2 Technical Rounds → 1 Client Round → HR Round
Keywords
AI Engineer | Generative AI | GenAI | LLM | Large Language Models | RAG | AI Agents | Python | TypeScript | Machine Learning | APIs | Microservices | Kubernetes | Docker | CI/CD | AWS | Azure | GCP | Vector Database | Hybrid Search
Skills: advanced retrieval techniques,kubernetes,ai/ml frameworks,vector databases,hybrid search,apis,distributed systems,ai roles,azure,typescript,rag pipelines,aws,artificial intelligence strategy,software engineering,python,microservices,llms,ci/cd pipelines,agentic ai,docker,devops
Sourced from foundit
Section · 02
Skills
DockerAI ML frameworks and librariesKubernetesHybrid search and advanced retrieval techniquesCI/CD PipelinesDistributed Systemsapisvector databasesRAG PipelinesDevOps practicesLarge Language Models (LLMs)PythonTypescriptMicroservices