Hands-on AI Technical Lead

AllysAI is seeking a hands-on AI Technical Lead to take ownership of enterprise AI systems, focusing on production large language model (LLM) deployments. This role involves leading a team of engineers through the full lifecycle of AI solutions—from architecture and implementation to deployment and ongoing reliability. You will spend most of your time designing, coding, testing, and shipping robust AI systems while collaborating closely with client technical teams to ensure successful delivery. The ideal candidate will have a strong ability to select appropriate technical approaches, anticipate potential failure points, and build dependable systems that handle sensitive data securely in real-world environments.

Key Responsibilities
- Design system architecture by deciding when to apply deterministic workflows, retrieval-augmented generation (RAG), single or multi-agent setups, and clearly communicate the trade-offs behind model, framework, and infrastructure choices.
- Develop Python services, APIs, retrieval pipelines, tool integrations, and agent workflows, including multi-channel processing (MCP) where applicable.
- Build document AI pipelines involving OCR, data extraction, classification, and cross-document validation, with robust handling of missing, conflicting, or uncertain information.
- Own system evaluation and robustness by creating representative test datasets, measuring retrieval and output quality independently, investigating failures, and establishing regression tests and release criteria.
- Manage deployment and operations by selecting appropriate client-controlled cloud or on-premises deployment methods, and oversee monitoring, latency, cost, reliability, and recovery processes.
- Integrate security into system design by enforcing access controls, data boundaries, protecting sensitive information, and controlling agent permissions.
- Lead delivery efforts by distributing tasks among engineers, conducting code reviews, setting technical standards, and collaborating with client teams through integration, testing, and production handover.

Required Qualifications
- Minimum of 5 years of professional software engineering experience, including at least 2 years working on production LLM or generative AI systems actively used by end users.
- Strong proficiency in Python and backend development, encompassing APIs, databases, integrations, and automated testing frameworks.
- Hands-on experience with RAG, vector search, re-ranking, structured output generation, and orchestration of agents and tools.
- Practical expertise in evaluating AI systems beyond demos, including test-set design, error analysis, measurable quality metrics, and production safeguards.
- Experience deploying systems using Docker, CI/CD pipelines, monitoring tools, and secure deployment best practices.
- Demonstrated leadership skills with the ability to guide engineers while remaining actively involved in coding and implementation.
- Excellent communication skills in English, capable of discussing architecture, delivery risks, and technical trade-offs with clients.
- A disciplined approach to AI-assisted development, able to articulate the coding tools used, their benefits, and methods for verifying generated code.

Preferred Qualifications and Benefits
- Experience with Azure services such as Azure OpenAI, AI Search, Document Intelligence, and API Management; strong knowledge of AWS or Google Cloud Platform is also valuable.
- Background in regulated industries like banking, pharmaceuticals, healthcare, or government sectors.
- Familiarity with private networking, locally hosted models, restricted connectivity environments, or on-premises deployments.
- Expertise in production document workflows involving complex layouts, multilingual content, or human-in-the-loop review processes.

AllysAI offers competitive compensation aligned with experience and role scope, flexible time off, and the opportunity for hands-on technical ownership with direct client engagement. You will contribute to building reusable AI capabilities deployed across multiple enterprise environments, gaining exposure to cutting-edge AI-native operational systems. This is a fully remote, full-time position ideal for candidates passionate about leading AI innovation in mission-critical settings.