Lead AI Engineer
Lead AI Engineer
Jade Global5-8 Years
- Posted 3 hours ago
- Be among the first 10 applicants
Job Description
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: 5–8 years of hands-on software engineering experience, with 3+ 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
OpenAI
workflow orchestration engines
LlamaIndex
About Company
Skills:
twilio , PostgreSQL, Prometheus, Grafana, Redis, Pytorch, Docker, Apache Kafka, Webrtc, Python, Kubernetes, TTS frameworks, LangChain, HuggingFace, Go, Exotel, vLLM, GRPC, OpenTelemetry, Temporal, LlamaIndex
Skills:
Git, Docker, System Design, data structures, Restful Apis, Python, Kubernetes, vector search, embeddings, agentic AI, Generative AI, AI governance principles, LLM APIs, performance optimization, RAG pipelines
Skills:
Databases, Apis, Docker, Pi, FastAPI, Python, Kubernetes, LangChain, GenAI, Claude Code Skills, multi-agent architectures, Hermes Agent, cloud platforms, Claude Code, CI CD, LangGraph, RAG, MCP, Evals, production deployments, agent orchestration
Skills:
Computer Vision, Deep Learning, Python Programming, AWS, Pytorch, Azure, Gcp, Nlp, LLM fine-tuning, LLMs, Vertex AI, guardrails, Document Processing, AI ML systems, Hugging Face, Agentic AI solutions, vector hybrid search, advanced prompt engineering techniques, RAG, observability monitoring
Skills:
Gcp, Distributed Systems, Azure, AWS, LangChain, Tool Calling, Model Context Protocol, orchestration tools, workflow automation platforms, Generative AI frameworks, Agentic AI, microservice integration, Prompt Engineering, LlamaIndex, RAG architectures