Cloud, Artificial Intelligence, Data Engineering

Skill to Evaluate

Cloud, Artificial Intelligence, Data Engineering

Experience

6 to 10 Years

Location

Bengaluru

Job Summary:

We are looking for an experienced Cloud AI and Data Engineer with a robust background in cloud-native data solutions, AI/ML engineering, and emerging Generative AI (GenAI) technologies. The ideal candidate will have 68 years of hands-on experience in building robust data platforms, deploying scalable ML models, and integrating GenAI solutions across cloud environments.

Key Responsibilities:

- Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.g., AWS Glue, Azure Data Factory, GCP Dataflow)
- Design and implement production-ready GenAI applications using services like Amazon Bedrock, Azure OpenAI, or Google Vertex AI
- Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions
- Integrate GenAI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns
- Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and GenAI capabilities
- Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments
- Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI models




- Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies
- Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards

Required Skills & Qualifications:

- 68 years of experience in data engineering or machine learning engineering in cloud environments (AWS, Azure, or GCP)
- Proficiency in Python and SQL; familiarity with PySpark, Java, or Scala is a plus
- Experience working with GenAI models such as GPT, Claude, or custom LLMs via cloud services (e.g., Bedrock, Azure OpenAI, HuggingFace)
- Hands-on with prompt design, fine-tuning, vector stores (e.g., FAISS, Pinecone), and knowledge base integrations
- Experience with MLOps and LLMOps tools (e.g., MLflow, LangChain, SageMaker Pipelines, Weights & Biases)
- Solid understanding of containerization (Docker), orchestration (Kubernetes), and microservices
- Knowledge of data lake/warehouse platforms such as S3, Snowflake, BigQuery, or Redshift
- Familiar with governance frameworks, access control, and responsible AI practices

Preferred Qualifications:

- Certifications in Cloud AI/ML platforms (e.g., AWS Certified Machine Learning, Azure AI Engineer)
- Experience building RAG systems, vector database search, and multi-turn conversational agents
- Exposure to real-world GenAI use cases like code generation, chatbots, document summarization, or knowledge extraction
- Knowledge of OpenAPI, JSON schema validation, and API lifecycle tools

📌 Cloud AI & Data Engineer (Bengaluru)
🏢 Acesoft Labs
📍 Bengaluru