Tech Lead

As a Tech Lead /Solution Architect (.Net/Python & Generative AI), you will play a

pivotal role in designing and leading the delivery of enterprise-grade AI-driven solutions.

This position requires deep technical acumen across cloud-native architectures,

Generative AI frameworks, and large-scale systems integration. You'll serve as the

bridge between product vision and technical execution, defining architectures that

leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and

cloud-native microservices to drive business transformation

The ideal candidate combines hands-on backend engineering skills

(.Net/SQL/AWS/Python) with architectural leadership in AI solutioning—capable of

translating abstract business goals into scalable, secure, and high-performance GenAI

applications in the cloud.

Key Responsibilities:

Architectural Leadership

 Design and implement end-to-end enterprise AI solutions leveraging .Net and/or

Python.

 Define reference architectures and solution blueprints for Generative AI use cases,

including RAG, document intelligence, conversational systems, and AI copilots.

 Develop scalable backend systems and APIs integrating with LLM orchestration

frameworks (e.g., FastAPI, LangChain, LangGraph) and AWS Bedrock.

 Lead architectural design reviews, ensuring system robustness, scalability, and

compliance with enterprise standards.

Generative AI Integration

 Architect and deploy LLM-based solutions utilizing frameworks such as LangChain,

LangGraph, and AWS Agents for Bedrock.

 Define data ingestion, embedding, and retrieval workflows supporting RAG-based

pipelines with vector databases (e.g., Pinecone, FAISS, ChromaDB).

 Implement prompt orchestration, context caching, and fine-tuning workflows to

optimize model performance and accuracy.

 Evaluate and integrate cutting-edge GenAI frameworks, managing proofs-of-concept

(POCs) to validate solution feasibility and ROI.

Collaboration & Delivery

 Partner with Product Managers, Data Scientists, and ML Engineers to translate

business goals into scalable AI architectures.

 Drive cross-functional alignment on AI system design, deployment strategies, and

operational governance.

 Lead technical due diligence and vendor evaluations for AI tools, APIs, and cloud-native

services.

Cloud Architecture & Governance

 Architect and deploy AI workloads on AWS, leveraging services such as AWS Bedrock,

Lambda, ECS/EKS, SageMaker, Step Functions, S3, and CloudWatch.

 Design for security, cost optimization, and observability within GenAI workloads.

 Establish governance frameworks for AI model usage, monitoring, and lifecycle

management.

 Ensure compliance with enterprise data protection and AI governance policies.

Technical Skills & Stack Requirements:

 Programming Expertise: Advanced proficiency in .Net and Python for backend

architecture, API development, and service orchestration.

 Generative AI Frameworks: Deep hands-on experience with FastAPI, LangChain,

LangGraph, AWS Bedrock, and LLM orchestration pipelines.

 Cloud Platforms: Expert-level experience with AWS or Azure cloud architecture,

particularly Bedrock, Lambda, ECS/EKS, Step Functions, S3, and SageMaker and Azure

equivalents.

 AI Pipeline Design: Proven ability to design RAG architectures, embedding pipelines,

and vector search integrations (e.g., Pinecone, FAISS, ChromaDB).

 Prompt Engineering: Understanding of advanced prompt chaining, retrieval strategies,

and dynamic context management.

 Enterprise Architecture: Strong foundation in microservices, RESTful APIs, event-

driven design, and asynchronous message queues (Kafka, SNS/SQS).

 DevOps & CI/CD: Familiarity with containerization (Docker, Kubernetes), IaC

(Terraform/CloudFormation), and automated deployment pipelines.

 Security & Compliance: Knowledge of IAM, data encryption, secure API gateways, and

AI model governance standards.

Preferred Qualifications:

 Bachelor's or master's degree in computer science, AI/ML, or related field.

 6+ years of enterprise software experience, with at least 3+ years in AI or cloud solution

architecture.

 Demonstrated success leading GenAI solution design and implementation in enterprise

settings.

 Familiarity with Azure OpenAI, Anthropic Claude, or Google Vertex AI is a plus.

 Experience building AI-enabled enterprise SaaS or copilot platforms preferred.

 Knowledge of LLM fine-tuning, embeddings, or model hosting.

Soft Skills & Leadership Attributes:

 Strategic thinker with the ability to align AI architectures to business value.

 Excellent communication skills—able to articulate complex AI concepts to both technical

and non-technical stakeholders.

 Proven track record in technical leadership, mentoring, and influencing cross-functional

teams.

•  Entrepreneurial mindset with curiosity for emerging AI technologies and industry trends.