AI Lead / AI Architect

Tkxel LLC; Lahore; On-site; PKR 49,848,000 - 66,464,000; Full time

Job summary

Tkxel LLC is seeking an AI Lead / AI Architect with 7+ years of experience to drive enterprise AI initiatives and shape architecture. You will lead AI strategy, collaborate with product teams, and guide data scientists and engineers from concept to production deployment.

The role requires defining end-to-end AI architectures, evaluating technologies, and establishing patterns and governance for scalable, secure AI solutions across on-premises Kubernetes and cloud environments.

Qualifications

• Minimum of 7 years of experience in AI/ML, data science, software engineering, or related fields.
• Hands-on experience designing and delivering enterprise AI/ML solutions.

Responsibilities

• Define the AI/ML architecture and technical strategy for enterprise AI initiatives.
• Translate business objectives and use cases into scalable, secure, and production-ready AI solutions.
• Lead the design of end-to-end AI architectures, including models, data, APIs, applications, infrastructure, and integration components.
• Evaluate AI/ML technologies, frameworks, platforms, and models and recommend the most appropriate solutions.
• Establish reusable AI architecture patterns, standards, and best practices.
• Define technical approaches for traditional ML, Generative AI, LLMs, RAG, and AI Agents.
• Guide Data Scientists and AI/ML Engineers in model development, experimentation, evaluation, and productionization.
• Work with DevOps/MLOps teams to establish production deployment architectures across on-premises Kubernetes and cloud environments.

Job description

Tkxel is a leading softwaredevelopment company located in Reston, Virginia. We are committedto develop innovative software solutions for leading enterprisesin the world, helping them grow their businesses using latesttechnology solutions.

Job Description

AI Lead / AI Architect with a minimum of 7 years of experience in AI/ML, data science, software engineering, or related fields , including strong hands-on experience designing and delivering enterprise AI/ML solutions . Will provide technical leadership for AI initiatives, define AI architecture and solution patterns, and guide AI/ML solutions from business requirements through production deployment.

Key Responsibilities

Define the AI/ML architecture and technical strategy for enterprise AI initiatives.

Translate business objectives and use cases into scalable, secure, and production-ready AI solutions.

Lead the design of end-to-end AI architectures , including models, data, APIs, applications, infrastructure, and integration components.

Evaluate AI/ML technologies, frameworks, platforms, and models and recommend the most appropriate solutions.

Establish reusable AI architecture patterns, standards, and best practices .

Define technical approaches for traditional ML, Generative AI, LLMs, RAG, and AI Agents.

Work closely with Business Analysts and Product teams to assess AI use cases, technical feasibility, value, data requirements, and dependencies.

Guide Data Scientists and AI/ML Engineers in model development, experimentation, evaluation, and productionization.

Work with Data Engineers to define data architecture and pipelines required for AI/ML solutions.

Work with Backend and Frontend teams to integrate AI capabilities into enterprise applications.

Work with DevOps/MLOps teams to establish production deployment architectures across on-premises Kubernetes and cloud environments .

Define requirements for model serving, inference, scalability, monitoring, and lifecycle management.

Establish appropriate approaches for model versioning, deployment, monitoring, retraining, and rollback .

Ensure AI solutions meet requirements for security, performance, scalability, availability, and maintainability.

Identify technical risks, architectural constraints, dependencies, and technology gaps.

Lead technical design reviews and provide guidance on complex AI/ML architecture decisions.

Ensure AI solutions are aligned with enterprise architecture and security standards.

Provide technical leadership and mentorship to AI/ML and engineering teams.

Stay current with developments in Generative AI, LLMs, AI Agents, MLOps, and AI engineering and assess their relevance to the organization.

Generative AI G LLM

Design architectures for LLM-powered applications and enterprise Generative AI solutions.

Define appropriate approaches for:

• RAG
• Embeddings
• LLM orchestration
• AI Agents
• Tool/function calling
• Model routing and selection

Evaluate commercial and open-source models based on performance, cost, latency, security, and business requirements .

Design solutions that support multiple LLM providers or models where appropriate.

Establish approaches for LLM evaluation, monitoring, and quality measurement.

Address AI-specific concerns such as hallucination, data leakage, prompt injection, access control, and model reliability .

Guide teams in selecting appropriate frameworks such as LangGraph, LangChain, or similar AI application frameworks .

Design end-to-end architectures covering:

• Define appropriate model development and production environments.
• Establish patterns for real-time and batch inference.
• Define integration patterns for AI/ML models with enterprise applications and APIs.
• Ensure AI solutions can operate across on-premises, cloud, and hybrid environments .
• Design for scalability and high availability of AI/ML workloads.
• Define appropriate compute requirements, including CPU/GPU resources where applicable.
• Establish architecture patterns for AI/ML observability and monitoring.

AI Governance G Responsible AI

Define technical controls for AI security, privacy, governance, and responsible AI .

Establish appropriate human oversight for AI-powered decisions.