Senior AI Engineer
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Job Description
Senior AI Engineer2
Technical Skills
Technical Skills
- Engineering Stack: Strong hands-on proficiency in Python and/or .NET (C#, ASP.NET Core), Java, or Node.js.
- AI & GenAI: Practical experience with GenAI APIs (OpenAI, Azure OpenAI), LangChain, LlamaIndex, RAG patterns, or agentic workflow frameworks.
- Cloud & DevOps: Hands-on experience with AWS, Azure, or GCP—microservices, Docker, Kubernetes, and CI/CD pipelines (GitHub Actions, Azure DevOps).
- Automation: Exposure to workflow orchestration engines, RPA tools, or custom automation scripts.
- Enterprise Platforms: Familiarity with enterprise systems (Oracle, SAP, Salesforce, or ServiceNow) is a plus.
- Certifications: Cloud Certification (AWS, Azure, or GCP) at associate/developer level is a plus.
- Clear technical communication—able to explain code implementation to teammates and project managers.
- Collaborative team player accustomed to working across global/offshore time zones.
- Curious and self-motivated — proactively explores new AI tools, frameworks, and engineering patterns.
- Experience: 4–6 years of hands-on software engineering experience, with 2+ years as, Senior AI engineer
- Hands-on experience building and delivering enterprise-grade solutions across cloud, AI/ML, and application engineering.
- Experience working in client-facing delivery environments within IT services or consulting organizations is preferred.
- Hands-on Engineering & Delivery
- Write production-grade code to build component-level features and API integrations based on technical designs and blueprints.
- Actively contribute to daily engineering deliverables—developing backend microservices, driving unit testing, refactoring code, and resolving technical debt.
- Conduct peer code reviews to ensure code quality, performance, maintainability, and adherence to team engineering standards.
- Troubleshoot and resolve complex bugs, API integration issues, and performance bottlenecks within application microservices.
- Learn, implement, and integrate for AI-native feature— including GenAI integration patterns, agentic workflows, and intelligent automation
- Contribute to the development and maintenance of AI engineering frameworks, solution accelerators, and reusable technical assets.
- Evaluate and experiment with new tools, APIs, and platforms in the AI and cloud-native space.
- Engage with client technical teams to understand system landscapes, integration requirements, and technical constraints.
- Propose pragmatic, technology-forward solutions to complex engineering challenges across application modernization, AI integration, and cloud migration.
- Support the Solution and Principal Architect in pre-sales activities including technical assessments, proof-of-concept design, and effort estimation.
- Develop and deploy cloud-native services on AWS, Azure, or GCP using containers (Docker, Kubernetes), serverless functions, and event-driven patterns.
- Implement intelligent automation components using workflow orchestration engines, RPA integrations, or custom AI-driven pipelines.
- Mentor junior engineers—supporting technical upskilling on AI tools, cloud platforms, and modern engineering practices.
- Contribute to Jade's internal community of practice through knowledge sharing, documentation, and participation in architecture discussions.
- Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related technical field is required.
More Info
Key Skills
GenAI APIs
Cloud Certification
Azure OpenAI
GitHub Actions
LangChain
RAG patterns
ASP.NET Core
agentic workflow frameworks
OpenAI
workflow orchestration engines
LlamaIndex
About Company
Skills:
Rest API Development, Gcp, FastAPI, Azure, Python, AWS, Retrieval Pipelines, Scalable Distributed Systems, Vector Databases Embeddings, RAG Architecture Applications, System Solution Architecture, Generative AI LLMs, Data Ingestion Preprocessing
Skills:
Rest Apis, Microservices, Azure Databricks, Cloud Services, Kubernetes, Python, Docker, AI orchestration frameworks, Generative AI solution design, Developing agentic AI workflows, AI Engineering Generative AI, Data pipelines, Event-driven architectures, Large Language Model LLM application development, Feature engineering, Building deploying and maintaining AI-powered applications, CI CD pipelines, Software Engineering Application Development, Prompt engineering
Skills:
object detection , Image Processing, Tensorflow, Nlp, Python, Ml, Rest API Development, Opencv, Faster R-CNN, Ai, YOLO, NoSQL database design, Computer vision models, Statistical Techniques, RDBMS design, Classification
Skills:
Websocket, FastAPI, Azure, Python, CrewAI, LangChain, multi-agent frameworks, streaming APIs, Qdrant, SSE, RAG implementation, Hugging Face, sentence-transformers, embedding models, LangGraph, vector stores, FAISS, LoRA, Milvus, OpenAI, ChromaDB, QLoRA
Skills:
Python, multimodal models, data pipelines, hallucination mitigation techniques, Mistral, MLOps tools, guardrails, RAG pipelines, Generative AI models, fine-tuning techniques, safety mechanisms, fine-tuning workflows, model monitoring, Haystack, LangChain, PEFT, instruction tuning, LLaMA, LLMs, Anthropic, prompt engineering, CI CD pipelines, LoRA, OpenAI, LlamaIndex