Senior Applied Ai Engineer

Senior Applied AI Engineer

Location:

Onsite / Hybrid 

Department:

Engineering & Delivery 

Role Type:

Full-Time / Senior Individual Contributor

About the Role

We are looking for a

Senior Applied AI Engineer

to design, build, and deliver production-ready AI agents and automation workflows across a variety of client and internal use cases. This is our first dedicated AI engineering hire, responsible for establishing how Logiciel approaches applied AI from early prototypes through to hardened production systems.

You will work closely with engineering teams, help shape solution architecture, build demos and proofs of concept where needed, and ultimately deliver reliable, maintainable AI-driven systems. You will also support pre-sales discussions by evaluating feasibility, estimating effort, and guiding what commitments we make.

This is an applied engineering role. We want someone who can build, integrate, iterate, and ship.

What You’ll Do / Own

1. Build Applied AI Agent Systems

You will design and implement multi-step agents, reasoning flows, and automation workflows that interact with internal and external systems.

Responsibilities:

• Implement agent logic, tooling, and workflow orchestration.
• Develop retrieval pipelines and knowledge-grounding workflows.
• Build structured extraction flows using LLMs and transformation logic.
• Convert prototypes into production-ready services with monitoring and predictable behavior.
• Ensure agents are explainable, observable, and have well-defined failure and fallback paths.

2. Architect and Integrate End-to-End Solutions

You will connect backend services, data sources, and AI components into cohesive systems.

Responsibilities:

• Define architecture for applied AI solutions using TypeScript/Node and Python.
• Integrate agents with APIs, databases, event systems, and existing product surfaces. Familiarity with Agent integration protocols like MCP or A2A is expected here as well.
• Establish patterns for prompt management, model selection, retrieval, and verification.
• Implement evaluation pipelines to monitor accuracy, drift, and reliability.
• Build reusable modules and internal tooling that accelerate future AI development.

3. Prototypes, Demos and Pre-Sales Support

You will help shape early opportunities and ensure we commit to what we can deliver.

Responsibilities:

• Build functional prototypes and demos to validate ideas.
• Assess feasibility, complexity, and potential risks of proposed AI features.
• Collaborate with sales and delivery teams on scope and technical approach.
• Provide guidance on trade-offs between different model and architecture choices.
• Help create realistic timelines and delivery plans.

4. Technical Leadership and Mentorship

You will uplift Logiciel’s engineering capability in applied AI.

Responsibilities:

• Mentor backend engineers on AI patterns, workflows, and integration techniques.
• Introduce practices for testing, evaluation, observability, and versioning.
• Share knowledge on effective prompting, model behavior, and tool usage.
• Help establish Logiciel’s standards for applied AI solution design and delivery.

What Success Looks Like

• AI-driven features and agents are delivered predictably and behave reliably in production.
• Retrieval and grounding workflows are well-tuned, observable, and continuously improving.
• Prototypes support better decision-making and stronger pre-sales conversations.
• Engineering teams understand how to integrate AI components responsibly and effectively.
• Logiciel develops a consistent, repeatable approach to applied AI delivery.

Skills and Experience (Non-Negotiable)

• 6–9 years of software engineering experience with strong backend fundamentals.
• Proven experience building and shipping applied AI systems or agents in production.
• Strong hands-on experience with TypeScript/Node and Python.
• Experience with agent frameworks or custom orchestration patterns.
• Strong understanding of retrieval workflows, embeddings, chunking, and evaluation methods.
• Experience working with vector databases and related tooling.
• Decent understanding of  underlying infrastructure and production operations i.e LLMOps
• Ability to design and integrate multi-step workflows with external systems and APIs.
• Comfortable working from prototype to production with attention to reliability and observability.
• Ability to break down ambiguous ideas and propose clear, technically grounded solutions.
• Strong communication skills, especially when explaining feasibility and technical trade-offs.

Nice to Have

• Experience with speech-to-text or text-to-speech pipelines.
• Familiarity with workflow engines or orchestration tools.
• Experience with evaluation frameworks or custom benchmarking pipelines.
• Exposure to model monitoring, versioning, or lightweight MLOps practices.
• Prior involvement in pre-sales or client-facing technical discussions.
• Experience mentoring engineers on applied AI practices.
• Experience with no code tools like n8n `

Who You Are

• A pragmatic engineer who prefers delivering working systems over theoretical research.
• Comfortable operating in ambiguity and iterating quickly on early concepts.
• Able to balance exploratory work with production-grade engineering.
• Someone who thrives in fast-moving environments where people wear multiple hats.
• Excited to shape Logiciel’s early applied AI capabilities and engineering foundations.

Why Join Us

• Become the foundational hire for Applied AI at Logiciel.
• Own high-impact projects from design to deployment.
• Influence architecture, patterns, and future team growth.
• Work in a culture that values engineering clarity, autonomy, and tangible results.