Senior Applied AI Engineer / AI Technical Lead / Architect

Senior Applied AI Engineer / AI Technical Lead / Architect

100% Remote Working (USA) - Eastern Timezone working hours

Contract-To-Hire - Initial Contract circa 6 months, transitioning into a permanent role

Initial Contract rates & Permanent Salary (If offered at a later date) - Fully Negotiable

**Suitable candidates will need to be legally authorized to work in the USA - H1B Visa, Sponsorship etc are not being accepted for this role***

We are seeking a highly experienced Senior Applied AI Engineer / AI Technical Lead / Architect to lead the design and development of enterprise-grade Generative AI solutions. This role combines hands-on engineering, solution architecture, and technical leadership, focusing on building scalable AI systems that solve complex real-world problems.

You will own the end-to-end technical design and implementation of AI solutions, guiding projects from early experimentation through production deployment. The position requires deep expertise in LLMs, retrieval systems, agentic workflows, and enterprise AI architecture, along with the ability to mentor engineering teams and establish best practices for applied AI development.

This role is ideal for someone who enjoys building systems, making architectural decisions, and enabling teams to deliver high-quality AI solutions at scale.

Key Responsibilities

AI Solution Architecture & Ownership

• Own the end-to-end technical design of applied AI solutions across multiple business domains.
• Design scalable LLM-based architectures, including:
• Retrieval-Augmented Generation (RAG) pipelines
• Agent-based workflows and tool orchestration
• Human-in-the-loop checkpoints
• Define integration patterns between AI services and enterprise systems such as policy administration, claims, and CRM platforms.
• Establish reference architectures for POC, pilot, and production deployments.

Hands-On AI Development

• Build end-to-end AI prototypes and production systems in Python.
• Implement and optimize:
• Prompt engineering strategies
• Retrieval pipelines and embeddings
• AI agents and tool integrations
• API services and model inference layers
• Evaluate and prototype emerging GenAI technologies including:
• GPT-4
• Claude
• Gemini
• Refactor and enhance existing AI codebases to meet enterprise standards.

Architecture & Platform Development

• Design scalable AI infrastructure using Azure OpenAI Service and Azure cloud services.
• Define data flows, API contracts, and system integration patterns.
• Establish reusable frameworks and AI development patterns to accelerate delivery across projects.
• Implement observability, monitoring, and performance optimization across AI systems.

Technical Leadership & Team Enablement

• Provide technical direction to an offshore engineering team.
• Conduct architecture reviews, code reviews, and deep-dive technical sessions.
• Break complex AI architectures into clear development tasks.
• Mentor engineers on best practices for applied AI, LLM systems, and production ML engineering.

Decision-Making & Technical Strategy

• Evaluate when to use GenAI vs traditional machine learning or rule-based approaches.
• Make trade-off decisions across:
• accuracy vs speed
• cost vs capability
• autonomy vs control
• determinism vs flexibility
• Ensure solutions remain explainable, reliable, and enterprise-safe.

AI Governance & Risk Alignment

• Implement guardrails for:
• PII handling
• prompt safety
• output validation
• data security boundaries
• Partner with security, legal, and compliance teams to ensure responsible AI deployment.
• Design fallback mechanisms and failure-handling strategies.

Required Skills & Experience

• 7+ years in software engineering or AI/ML engineering roles.
• 3+ years working with LLMs, Generative AI, or advanced NLP systems.
• Strong Python development experience building production systems.
• Deep understanding of Retrieval-Augmented Generation architectures.
• Experience designing AI agents, tool orchestration, or multi-step AI workflows.
• Experience with cloud-based AI infrastructure (Azure preferred).

Browse our curated collection of remote jobs across all categories and industries, featuring positions from top companies worldwide.

• Familiarity with vector databases, semantic search, and embeddings.
• Experience designing secure and scalable enterprise AI systems.
• Strong architectural thinking and ability to lead technical decision-making.
• Experience mentoring or leading engineering teams.

Preferred Experience

• Experience in regulated industries such as insurance, financial services, or healthcare.
• Hands-on experience with vector search systems and knowledge retrieval.
• Familiarity with evaluation frameworks for LLM outputs and model performance.
• Experience building reusable AI platforms or internal developer frameworks.

Key Performance Indicators

• Deliver 8+ production-ready AI features or enhancements per quarter with minimal post-release defects.
• Achieve 70%+ reuse of standardized AI components and architecture patterns across new projects.
• Maintain 90%+ alignment between recommended technical approaches and successful implementation outcomes.

What Success Looks Like

Within the first 6–9 months, you will have:

• Established consistent AI architecture patterns across projects
• Accelerated the transition from proof-of-concept to production
• Enabled engineering teams to deliver AI solutions faster and more reliably
• Reduced architectural uncertainty across AI initiatives
• Increased stakeholder confidence in AI-powered systems

What This Role Does Not Own

To ensure focus on technical delivery, this role does not directly own:

• Product prioritization
• Business requirements documentation
• Data platform ownership
• Vendor contract negotiations
• Pure research projects without practical application

This is a high-impact technical leadership role for someone passionate about building real-world AI systems and shaping the future of enterprise AI applications.