Leyton CognitX is the AI & Tech Advisory of Leyton, bringing together a dynamic team of over 200 tech experts and data scientists. We specialize in delivering innovative AI and technology solutions that transform how organizations operate and compete.
Our approach combines strategic advisory services with custom development, enabling businesses to harness the power of AI and advanced technologies. We work closely with each client to design intelligent, streamlined solutions that address their specific challenges and align with their strategic objectives.
At Leyton CognitX , we believe that technology is more than just tools; it's a catalyst for meaningful organizational and technological transformation. Our mission is to empower companies to leverage AI and cutting-edge tech, turning complex challenges into opportunities for growth, efficiency, and innovation.
Company culture :
Leyton stands out for a strongly cooperative and people-centered culture, where trust, collaboration and employee well-being are key pillars. The company promotes a close management approach focused on support, empowerment and high-quality team relationships. This collaborative foundation is complemented by a significant innovation dimension, fostering initiative, creativity and agility. Competitive and organizational cultures play a more secondary role, providing structure, performance orientation and operational efficiency.
Job :
As an experienced AI Software Engineer, you will play a driving role within our multidisciplinary team (Data Scientists, DevOps, Consultants). You will be responsible for architectural design, development, and large-scale deployment of AI-based technology solutions for both internal and external clients. You will tackle complex, open-ended problems requiring sharp technical decisions, uncompromising engineering rigor, and a strong capacity for innovation.
Responsibilities :
Architecture & Development: Design, architect, and develop complete, scalable features and platforms (APIs, business logic, databases, security).
AI Engineering: Lead the implementation of complex AI systems in production: advanced RAG pipelines, LLM agent fleets, model fine-tuning and integration (OpenAI, Anthropic, open-source LLMs).
Quality & Clean Code: Champion best practices (SOLID principles, Clean Architecture, design patterns) and conduct thorough code reviews.
Reliability & Testing: Define the testing strategy (TDD, unit, integration, e2e, stress tests) to ensure flawless deployments.
MLOps & Cloud: Deploy, monitor, and optimize models and code in dedicated environments with robust CI/CD pipelines.
Client Facing & Advisory: Act as a technical expert with clients. Understand their business challenges, break down complex concepts, and defend your architectural decisions.
Mentoring: Support the growth and skill development of junior developers and DataLab interns.
Required Skills :
Fundamentals - Full Mastery Expected
System Design & Architecture: Ability to design distributed, scalable, and resilient systems. Strong command of architectural trade-offs.
Data Structures & Algorithms: Solid algorithmic expertise for performance optimization (Big-O, streaming and batch data processing).
Clean Code & Patterns: Strict application of SOLID principles and mastery of design patterns (including microservices and event-driven architectures).
CI/CD & DevOps: Advanced Docker, orchestration (Kubernetes is a plus), GitHub Actions / GitLab CI, Terraform / Infrastructure as Code.
APIs & Databases: Design of robust APIs (REST, gRPC, GraphQL). Optimization of relational (PostgreSQL) and non-relational databases (MongoDB, Redis, graph databases).
AI & Data - Technical Expertise:
LLM Integration & Ops (LLMOps): Advanced API integration, complex prompt engineering, token/cost management, streaming, continuous monitoring, and evaluation of models in production.
RAG & Agent Ecosystem: Proficiency with LangChain, LlamaIndex, or custom solutions. LangGraph. Large-scale implementation of Vector Stores (FAISS, Pinecone, Qdrant, Milvus). Advanced chunking and reranking strategies.
Information Retrieval: Solid understanding of search algorithms (TF-IDF, BM25, Cross-Encoders) and search engines (Elasticsearch).
Tech Stack - Tech Agnostic, with Strong Appetite for:
Engineering degree or Master's (Computer Science, Mathematics, Data Science) with 3 to 6 years of relevant experience.
Proven track record: You have already designed, developed, and deployed software solutions integrating AI (Machine Learning, NLP, or GenAI) with measurable business impact.
Problem-solving & Autonomy: Ability to take a vague business need and turn it into a solid technical architecture and finished product.
Communication & Leadership: Strong interpersonal skills to engage with demanding clients and the ability to rally a technical team.
Technological Watch: Insatiable curiosity for a fast-moving AI ecosystem.
Search for new things / novelty
Creativity
Need for reflection
Need for autonomy
Involvement at work
Ambition
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