Senior AI Engineer

About Logistiex

Logistiex is building intelligent supply chain and logistics technology solutions that help enterprises improve operational efficiency, visibility, automation, and decision-making.

As part of our next phase of innovation, we are developing an AI-native, Agentic Product Information Management (PIM) platform designed to automate and orchestrate product data workflows across catalogs, marketplaces, suppliers, ERP systems, and commerce ecosystems.

We are looking for a Product Manager who can lead the vision, execution, and scaling of this platform from concept to enterprise adoption.

About the Role

We are looking for a Senior AI Software Engineer to design, build, and scale intelligent systems powered by modern AI and machine learning technologies. This role combines strong software engineering fundamentals with hands-on expertise in AI model integration, data pipelines, distributed systems, and production-grade deployment.

The ideal candidate is passionate about solving real-world problems using AI, has experience building scalable AI applications, and can collaborate effectively across engineering, product, and business teams to deliver high-impact solutions.

You will play a key role in architecting AI-driven products, optimizing model performance, and establishing engineering best practices for scalable AI infrastructure.

Key Responsibilities

AI Application Development

• Design and develop AI-powered applications and services for production environments
• Integrate Large Language Models (LLMs), machine learning models, and AI APIs into business workflows
• Build scalable backend systems to support inference, orchestration, and real-time AI interactions
• Develop intelligent automation solutions using NLP, computer vision, recommendation systems, or predictive analytics

Model Integration and Optimization

• Fine-tune, evaluate, and optimize AI/ML models for performance, latency, accuracy, and cost efficiency
• Implement prompt engineering, RAG pipelines, vector search, and agentic workflows
• Work with foundation models such as OpenAI, Anthropic, Gemini, Llama, or open-source alternatives
• Improve model observability, monitoring, and feedback loops

Software Engineering and Architecture

• Build secure, scalable, and maintainable microservices and APIs
• Design distributed systems and cloud-native AI architectures
• Ensure high reliability, performance, and fault tolerance across AI systems
• Lead code reviews and establish engineering standards and best practices

Data and Infrastructure

• Develop and maintain AI data pipelines and feature engineering workflows
• Work with structured and unstructured datasets at scale
• Manage vector databases, caching systems, and data orchestration tools
• Collaborate with DevOps and platform teams for CI/CD and MLOps automation.

Cross-Functional Collaboration

• Partner with product managers, designers, researchers, and business stakeholders to define AI-driven solutions
• Translate business requirements into scalable technical architectures
• Mentor junior engineers and contribute to technical leadership within the organization
• Participate in architecture reviews and long-term technology planning.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, or related field
• 5+ years of software engineering experience with some experience focused on AI/ML systems
• Strong programming experience in Python and modern backend frameworks
• Experience deploying AI/ML systems into production environments
• Deep understanding of APIs, distributed systems, databases, and cloud infrastructure
• Experience working with LLMs, embeddings, vector databases, and AI orchestration frameworks
• Strong understanding of software design principles, testing, and system scalability

Preferred Qualifications

• Experience building AI agents, copilots, or autonomous workflows
• Familiarity with transformer architectures and modern ML frameworks
• Experience with fine-tuning and evaluation pipelines
• Background in NLP, search, retrieval systems, or recommendation engines
• Experience in high-growth startups or fast-paced engineering environments
• Contributions to open-source AI or engineering projects

Technical Skills

Programming and Frameworks

• Python
• FastAPI / Flask / Django
• Node.js or Go is a plus
• REST and GraphQL APIs

AI and ML Technologies

• OpenAI APIs
• LangChain / LlamaIndex
• Hugging Face Transformers
• PyTorch / TensorFlow
• RAG architectures
• Prompt engineering
• AI agent frameworks

Databases and Infrastructure

• PostgreSQL / MongoDB
• Redis
• Pinecone / Weaviate / ChromaDB / FAISS
• Kafka or event streaming systems

Cloud and DevOps

• AWS / GCP / Azure
• Docker and Kubernetes
• CI/CD pipelines
• Terraform is a plus

Monitoring and Analytics

• ML observability tools
• Logging and tracing systems
• Performance monitoring dashboards

Key Competencies

• Strong system design and architecture skills
• Product-oriented engineering mindset
• Ability to solve ambiguous and complex technical problems
• Excellent communication and collaboration skills
• High ownership and accountability
• Strong debugging and optimization capabilities
• Continuous learning mindset in rapidly evolving AI ecosystems

Success Metrics

Success in this role will be measured by:

• Reliability and scalability of AI systems in production
• AI feature adoption and business impact
• Model performance, latency, and cost optimization
• Engineering quality and deployment velocity
• System uptime and operational efficiency
• Contribution to technical innovation and team capability

Reporting Structure

• Reports to: Engineering Manager / Head of AI Engineering
• Collaborates with: Product, Data Science, Platform Engineering, DevOps, and Design teams

Compensation and Benefits

• Competitive salary and performance bonuses
• Equity or ESOP opportunities where applicable
• Health and wellness benefits
• Flexible work arrangements
• Learning and conference budget
• Access to cutting-edge AI tooling and infrastructure

Ideal Candidate Profile

The ideal candidate is an engineer who combines deep technical expertise with practical product thinking. They should be comfortable building production-grade AI systems, making architectural decisions, and balancing experimentation with engineering discipline. A successful Senior AI Software Engineer is proactive, highly collaborative, and excited about building intelligent systems that create measurable business value

Location: Hybrid

Employment Type: Full-time