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.
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.
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.
