Gen AI Engineer_Danske
Infosys · Bengaluru · onsite · Posted 71d ago
Undisclosed5–7 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
Educational Requirements
Bachelor of Engineering,BTech,MCA
Service Line
Data Analytics Unit
Responsibilities
- Design and develop Generative AI / LLM-based applications for enterprise use cases such as chatbots, summarization, document intelligence, search, QA, code assistants, and workflow automation.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using embeddings, vector databases, chunking, retrieval strategies, and prompt orchestration.
- Work with foundation models / LLMs from providers such as OpenAI, Anthropic, Cohere, Hugging Face, AWS Bedrock, or open-source models.
- Develop robust backend services and APIs to integrate GenAI solutions into enterprise platforms and applications.
- Fine-tune, evaluate, and improve model responses through prompt engineering, guardrails, grounding, and performance optimization.
- Build scalable AI pipelines on AWS or Databricks for training, experimentation, deployment, and monitoring.
- Collaborate with Data Science, ML Engineering, Application Engineering, and Product teams to productionize GenAI use cases.
- Ensure best practices in model deployment, observability, security, governance, and responsible AI.
- Contribute to architecture discussions, PoCs, reusable frameworks, and accelerators for GenAI adoption.
Additional Responsibilities:
- Cloud / Platform SkillsCandidate should have hands-on experience in either AWS or Databricks:AWS Bedrock, SageMaker, Lambda, ECS/EKS, S3, API Gateway, CloudWatch, IAM
- Experience deploying scalable AI/ML workloads on AWS OR Databricks - Databricks notebooks, MLflow, Model Serving, Delta Lake, Unity Catalog
- Experience building and deploying AI/ML / GenAI use cases on Databricks platform
- Exposure to MLOps / LLMOps concepts
- Knowledge of model monitoring, evaluation, experimentation, and versioning
- Experience with Docker, Kubernetes, CI/CD pipelines
- Familiarity with guardrails, AI safety, content filtering, and governance
- Exposure to multimodal AI, agentic workflows, or autonomous AI systems
- Understanding of structured/unstructured data processing pipelines
Technical and Professional Requirements:
- Strong hands-on experience in Python
- Good experience with Generative AI / Large Language Models (LLMs)
- Solid understanding of NLP, embeddings, transformers, prompt engineering, and LLM application design
- Experience building RAG pipelines
- Hands-on experience with orchestration frameworks such as LangChain / LlamaIndex / Semantic Kernel / AutoGen / CrewAI / LangGraph
- Experience with vector databases such as FAISS, Pinecone, Chroma, Weaviate, Milvus, Elasticsearch/OpenSearch
- Exposure to REST APIs / FastAPI / Flask for serving AI applications
- Strong understanding of ML lifecycle, deployment, testing, and performance tuning
Preferred Skills:
- Technology->AI-Generative AI->Generative AI - Basic->retrieval augmented generation (rag)
- Technology->AI-Generative AI->Generative AI for Data Analytics
- Technology->AI-Data science->Databricks Machine Learning
Sourced from naukri
Skills
kerasimage processingneural networksComputer Visiontext miningNatural Language ProcessingOpencvPattern recognitionTensorflowPythonDeep LearningPredictive ModelingData ScienceArtificial IntelligenceMachine Learning
About Infosys
Infosys
IT Services & Consulting
323.6k+
employees
1981
45 years old
Bengaluru/Bangalore, Karnataka
India
About
Infosys is a global leader in next-generation digital services and consulting.
Industries
IT Services & ConsultingConsulting
Employee ratings
48,765 reviews
3.5/ 5
Culture
3.6
Career growth
2.6
Work-life
3.6
Employees rate it well for
Salary10252Work Life Balance6251Work Culture5404Learning4530Appraisal3780
Find them on