We are seeking an experienced LLM & Agentic Systems Engineer to join our AI squad at our company. This role blends deep hands-on engineering with architectural responsibility and client-facing advisory work. You will design, build, and operate production-grade LLM and multi-agent systems, working on both greenfield initiatives and the evolution of existing GenAI platforms. You will play a key role in shaping technical direction, best practices, and delivery standards across the GenAI practice.
Key Responsibilities
GenAI Development & Implementation
Build end-to-end GenAI solutions from POC through production deployment
Design and implement backend microservices architectures for GenAI applications using Python
Design, implement, and maintain production-grade Python services with a focus on code quality, performance, and reliability
Architect and develop multi-agent systems, orchestration layers, and autonomous workflows
Integrate and optimize LLMs and GenAI APIs across complex systems
Evaluate and improve system performance, scalability, reliabililty, and cost efficiency
Client Engagement & Advisory
Lead technical discussions with clients and translate business needs into technical architectures Present GenAI solutions, design decisions, and trade-offs to technical and non-technical stakeholders Provide strategic technical guidance on GenAI adoption and system design
Cloud & Platform Ownership
Deploy and manage GenAI systems across GCP, Azure, and AWS Leverage cloud-native AI services (Vertex AI, Azure OpenAI, SageMaker, etc.) Own production environments, monitoring, and operational excellence
Continuous Learning & Practice Development
Evaluate emerging GenAI models, frameworks, and techniques Define and refine best practices for GenAI system development and deployment Contribute to internal accelerators, methodologies, and knowledge sharing.
Requirements: Technical Expertise
Advanced proficiency in Python for backend development and AI systems Deep understanding of large language models and generative AI techniques Hands-on experience designing and implementing multi-agent architectures Advanced prompt engineering and orchestration strategies Strong background in microservices architecture, API development, and production system design Hands-on experience with at least one major cloud platform (GCP, Azure, or AWS)
Professional Experience
2-3+ years of experience in AI/ML development with significant GenAI project exposure Proven experience deploying and maintaining AI systems in production Client-facing experience in technical consulting or solution delivery roles
Advantages
Hands-on experience developing directly against LLM provider SDKs and APIs (e.g., OpenAI, Anthropic, Google), including tool/function calling, streaming, and advanced orchestration patterns. Docker and Kubernetes experience OCR systems and document intelligence experience Data pipeline development and maintenance experience
Education & Background
Bachelors or Masters degree in Computer Science, AI, Machine Learning, or related field (or equivalent demonstrated industry experience)
Soft Skills
Strong problem-solving and analytical capabilities Excellent technical communication skills Ability to collaborate effectively across teams Adaptability in fast-paced, evolving technical environments Consulting mindset with strong client focus.
This position is open to all candidates.