Culture and benefits
What we offer to our employees
At ZegaSoftware, we pride ourselves on creating a work environment that prioritizes the wellbeing and development of our employees.
Learn why ZegaSoftware Apply to jobs!
Currently hiring Mid/Senior software developers, with a variety of competences
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AI Engineering Lead
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Posted 4 weeks ago
Responsibilities:
Technical Strategy & Architecture
- Develop a scalable and modular AI architecture that integrates seamlessly with existing customer platforms;
- Define and implement best practices for AI model deployment, data processing, and cloud infrastructure;
- Establish a clear roadmap for AI-driven capabilities, ensuring alignment with business goals.
AI & Data Engineering
- Design and implement Retrieval-Augmented Generation (RAG) pipelines and AI-driven data processing workflows;
- Design and develop complex agent-based solutions;
- Develop and optimize AI models tailored to enhance automation, personalization, and insights for client users;
- Ensure the integration of structured and unstructured data sources into AI workflows;
- Establish data governance frameworks, security models, and compliance strategies for AI usage.
Solution Development & Implementation Planning
- Collaborate with UX and product teams to define AI-powered user experience improvements;
- Identify and implement technical accelerators to optimize development speed and platform efficiency;
- Define technical milestones, effort estimations, and cost evaluations for implementation.
Collaboration & Stakeholder Management
- Work closely with product managers, designers, and engineers to align technical solutions with business needs;
- Provide technical leadership to engineering teams, guiding them in AI model deployment and system scalability;
- Engage with stakeholders to validate architectural decisions and refine technical requirements.
Performance Optimization & Scalability
- Establish monitoring frameworks for AI model performance, system reliability, and infrastructure scalability;
- Optimize AI pipelines and data processing layers to ensure real-time insights and efficient workflows;
- Address system bottlenecks and propose enhancements to improve user experience and cross-platform integrations.
Technical Expertise
- Proven experience as an AI Tech Lead or ML Engineer, ideally in customer-facing, production-deployed projects;
- Solid understanding of deep learning concepts, supervised / unsupervised / self-supervised / reinforcement learning;
- Solid understanding of Large Language Models, Transformers architecture, self-attention, mixture of experts, and embedding models;
- Proven experience with advanced Retrieval Augmented Generation, vector DBs, and prompt engineering;
- Expertise with AI agents design, orchestration and optimisation;
- Experience with CrewAI, LangChain / LangSmith / LangGraph, and/or LlamaIndex;
- Experience with model fine-tuning;
- Hands-on data pre-processing experience;
- Strong Python expertise;
- Proficiency in ML frameworks such as PyTorch, TensorFlow, or similar;
- Experience with AWS development and deployment (ECS, Lambda, S3);
- Experience with at least one of the following cloud-based AI platforms (preferrably AWS): AWS SageMaker / AWS Bedrock / Azure ML;
- LLMOps expertise;
- Familiarity with Docker and Kubernetes.
Leadership & Communication
- Strong ability to translate technical concepts into business-impact discussions;
- Experience leading AI engineering teams and working in cross-functional environments;
- Track record of working with product and business teams to define AI-driven solutions.
Strategic & Problem-Solving Skills
- Ability to assess existing systems, identify gaps, and develop AI-driven enhancements;
- Experience in defining and implementing AI strategies for enterprise-grade products;
- Strong analytical mindset with a focus on performance optimization and data-driven decision-making.
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Senior Python Developer
Apply nowPosted 4 weeks ago
Role Summary
Join the AI Platform Team to build backend services and automation for a large-scale
Azure-based data & AI platform. You’ll develop Python microservices, integrate with Azure
AI/ML and enable secure, scalable AI workloads across the enterprise.
Responsibilities
● Develop backend APIs and microservices in Python (FastAPI/Django/Flask);
● Build automation for AI environments, ML workflows, and platform tooling;
● Integrate with Azure services: Azure ML, Databricks, ADLS, Key Vault, AAD;
● Use IaC (Pulumi/Bicep/Terraform) to provision cloud resources;
● Contribute to CI/CD pipelines and implement testing, monitoring, and logging;
● Collaborate with data scientists, ML engineers, architects, and DevOps teams.
Requirements
● 5+ years Python development experience;
● Experience with Azure AI services and backend API development;
● Understanding of CI/CD and containerization (Docker);
● Strong problem-solving and communication skills.
Nice to Have
● AI Azure experience, Databriks, MLOps experience;
● Azure certifications.
Context
You will help build a cloud-native AI platform for a German automotive OEM, integrating Azure
ML, Databricks, and OpenAI to support enterprise-scale AI and analytics.
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Solution and Data Architect
Apply nowPosted 4 weeks ago
Key Responsibilities:
Architectural Oversight:
Own and evolve the overall solution architecture, including application, data, integration, and security layers, ensuring alignment with Wolseley’s IT policies and cloud infrastructure (Oracle/Azure)
Data Architecture Leadership:
Design and maintain the future-state data architecture, supporting automated quote intake, product resolution, pricing, stock availability, and order fulfilment.
Integration and Data Flow:
Architect seamless integration between Wolseley APIs (product, pricing, stock, order submission) and the application’s operational store, catalogue index, and audit logs.
Governance and Compliance:
Define and enforce data governance frameworks, retention schedules, and compliance (GDPR, auditability), minimising PII and ensuring secure handling of sensitive data
AI/ML Enablement:
Enable ingestion and transformation of historical quote/order data for AI advisory features, product recommendations, and pricing guardrails. Collaborate with AI/ML engineers to support NLP-based product resolution and audit-driven enhancements.
Operational Readiness:
Provide documentation, training, and handover artefacts for operational support, monitoring, and troubleshooting. Ensure all features delivered are tested and meet acceptance criteria.
Stakeholder Engagement:
Work closely with business, sales, and IT stakeholders to clarify requirements, facilitate decision-making, and support pilot deployment and evaluation.
Essential Skills & Experience:
Proven Experience:
Demonstrable track record as a Solution and Data Architect in large-scale, cloud-based solutions (preferably B2B quoting domains).
Cloud Platforms:
Expertise in Oracle Cloud and/or Microsoft Azure, including data warehousing, integration, and analytics.
API Integration:
Deep understanding of secure API design, authentication (OAuth2, SSO), and data flow between distributed systems.
Data Modelling:
Strong skills in relational and NoSQL modelling, catalogue indexing, and operational data stores (PostgreSQL, Elastic/OpenSearch, etc.).
AI/ML Familiarity:
Experience supporting AI/ML initiatives, including NLP, product matching, and audit-driven enhancements.
Compliance & Security:
Knowledge of GDPR, data retention, encryption, and audit requirements for enterprise data solutions.
Tools:
Familiarity with Power Platform, observability stacks (OpenTelemetry, Application Insights, Grafana), and CI/CD pipelines (Azure DevOps, GitHub Actions, Terraform).
Desirable attributes:
Excellent communication and stakeholder engagement skills;
Analytical problem-solving and attention to detail;
Ability to work collaboratively in agile, cross-functional teams;
Experience with data governance in regulated environments.
Deliverables:
Oversight and evolution of the solution and data architecture;
Integration and mapping specifications for Wolseley APIs;
Data governance and compliance artefacts;
Operational support documentation and training materials;
Contributions to AI/ML enablement and audit frameworks;
Review and refinement of the existing Low Level Solution Design (LLD).
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Gen AI - Senior Developer
Apply nowPosted 4 weeks ago
Role Overview
We’re looking for a GenAI senior Developer to design, build, and deploy intelligent LLM-powered systems—from single-agent chatbots, copilots to complex multi-agent applications - at scale. We are particularly interested in candidates who have hands-on experience in taking GenAI applications from concept to production, especially within high-volume B2C environments. This role prioritizes individuals who understand the nuances of deploying, maintaining, and optimizing GenAI solutions for real-world users,beyond the scope of Proof-of-Concept (PoC) development. You will work across the full stack, integrating LLMs, microservices,vector databases, backend APIs, and modern cloud infrastructure.
Key Responsibilities:
1. GenAI Application Development & Deployment
Develop scalable, asynchronous microservices using Python (FastAPI) for chatbots, copilots, and agentic workflows;
Design event-driven architectures to support high concurrency, rate limiting, and real-time responsiveness;
Implement secure, versioned REST/gRPC APIs;
Use Pydantic, dependency injection, and modular coding practices for maintainability;
Proficient in working with databases using ORMs like SQLAlchemy;
Ensure observability using logging, metrics, tracing, and health checks;
Create responsive React.js frontends integrated via REST APIs or WebSockets;
Deploy applications on Cloud Run, GKE, using Docker, Artifact registry, CI/CD pipelines.
2. LLM-Powered Conversational Interfaces
Design and build LLM-powered chatbots, voicebots, copilots and other applications using LangChain or custom orchestration frameworks;
Integrate enterprise-grade LLM APIs (Gemini, OpenAI, Claude) for multi-turn, intelligent interactions;
Implement user session management and context/state tracking for personalized and continuous conversations;
Build RAG pipelines with vector databases, knowledge graphs to ground responses with external knowledge and documents;
Apply advanced prompt engineering (ReAct, Chain-of-Thought with tool calling) for precise and goal-oriented outputs;
Ensure performance in low-latency, streaming environments using WebSockets, gRPC, and SIP media gateways;
Perform fine-tuning of open-source LLMs (LLaMA variants) using techniques like SFT, LoRA, for cost-effective domain adaptation;
Optimize high-speed inference pipelines leveraging multi-GPU clusters (up to 8x H100s) to reduce latency and improve throughput.
3. Multi-Agent Systems & Orchestration
Create multi-agent systems & Implement orchestration patterns like supervisor-agent, hierarchical, and networked agents usingframeworks like ADK, Pydantic AI and LangGraph;
Use LangGraph for stateful workflows with memory, conditional branching, retries, and async execution;
Enable persistent context and long-term memory;
Monitor behavior, drift, and performance using observability tools;
Skilled in developing agents with ADK and A2A protocols & experienced in configuring custom and remote MCP servers.
Preferred Tech Stack:
Languages/Frameworks: Python, FastAPI, HTML, CSS, React.js, LangChain, LangGraph, Pydatic AI, ADK (Agent DevelopmentKit) LLMs & Agents: OpenAI - (GPT-4), Claude, Gemini, Mistral, LLaMA 3.2/4;
Databases: BigQuery, Redis, FAISS, Pinecone, SQLAlchemy, Chroma, GCP Vector search;
Protocols/APIs: REST, gRPC, WebSockets, OAuth2, OpenAPI, MCP, A2A.
Additional Good to have Tech Stack:
DevOps: Docker, GitHub Actions, Jenkins, GKE, Cloud Run;
Infra & Tools: GCP, Azure, Pub/Sub,Artifact Registry, NGINX, Langfuse, Postman, Pytest.
Culture and benefits
Why to join ZegaSoftware as an employee
At ZegaSoftware, we pride ourselves on creating a work environment that prioritizes the wellbeing and development of our employees. Here’s what we offer:
Competitive salaries
We recognize the value of your work and reward it accordingly.
Professional development
Access to courses, conferences, and certifications to help you develop your skills.
Flexible work environment
Balance between professional and personal life is essential to us.
Wellness programs
Activities and resources for your physical and mental well-being.
Collaborative teams
A culture based on collaboration, innovation, and mutual support.
Private health insurance
Comprehensive medical coverage.
Meal tickets
Daily meal tickets to support your well-being.
Team-building activities
Regular events to foster team spirit and camaraderie.
Modern office environment
Equipped with the latest technology and amenities.
