Lead Generative AI Engineer | QX Impact · Teeming.ai
QX Impact
QuaXigma provides AI-powered software and data analytics services that help businesses compete more effectively. It delivers through cloud-based SaaS products and AI application development, backed…
QuaXigma provides AI-powered software and data analytics services that help businesses compete more effectively. It delivers through cloud-based SaaS products and AI application development, backed…
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Job Summary:
We seek a highly experienced
Lead Generative AI Engineer
who focus on the development, implementation, and
engineering of Gen AI applications using the latest LLMs and frameworks. This role requires hands-on
expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional
skills in front-end technologies, data modernization, and API integration. The Lead Gen AI engineer will be responsible for building applications from the ground up, ensuring secure, robust, scalable, and efficient solutions.
Responsibilities:
Build GenAI tools that interface with structured SQL databases and unstructured data lakes to perform analysis, and generate real-time business intelligence. Work with NLP, text generation, and contextual comprehension tasks.
Implement sophisticated Retrieval-Augmented Generation (RAG) pipelines, "tool use" and "function calling" capabilities, allowing agents to interact with built tools and external platforms (ERP, CRM) as well as execute analytical and ML workflows, such as retraining demand forecasting models or recommending import tax rate adjustments.
Implement complex state machines and reasoning loops (using LangGraph or similar) to handle multi-step tasks like inventory rebalancing and logistics rerouting.
Build and maintain sophisticated, context-aware chatbots that handle complex user intents and transition seamlessly between automated assistance and data retrieval.
Evaluate and deploy open-source models (e.g., Llama 3, Mistral, Mixtral) using frameworks like vLLM, TGI, or equivalent to ensure data privacy, reduce latency, and lower API costs for heavy industrial workloads.
Oversee the end-to-end lifecycle of LLM applications, including prompt engineering, evaluation, and deployment on cloud infrastructure (Azure/AWS/GCP).
Implement rigorous validation frameworks to minimize hallucinations in data and ensure the reliability of business insights.
Skills & Requirements:
Personal Attributes:
Strong problem-solving skills with a passion for data architecture.
Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.
Highly collaborative, capable of working with cross-functional teams.
Ability to thrive in a fast-paced, agile environment while managing multiple priorities effectively.
Competencies:
Tech Savvy -
Anticipating and adopting innovations in business-building digital and technology applications.
Self-Development -
Actively seeking new ways to grow and be challenged using both formal and informal development channels.
Action Oriented -
Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.
Customer Focus -
Building strong customer relationships and delivering customer-centric solutions.
Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.
Why Join Us?
Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
Work on impactful projects that make a difference across industries.
Opportunities for professional growth and continuous learning.
Competitive salary and benefits package.
Application Details
Ready to make an impact? Apply today and become part of the QX impact team!
8+ years of experience in software engineering, including leading the architecture, development, and large-scale deployment of enterprise-grade AI/GenAI solutions across Finance, Supply Chain, or Manufacturing domains.
Expert proficiency with LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel to build complex, stateful AI workflows.
Deep expertise in Python and high-level proficiency in Vector Databases (Pinecone, Weaviate, Milvus) and orchestration tools like Docker and Kubernetes.
Proficiency in hosting and scaling AI-driven applications using Azure AI Foundry, Azure Web Apps, Container Apps, AKS, Azure Logic Apps, Service Bus, and Event Grid.
Strong understanding of Azure RBAC, Managed Identities, and Key Vault for secret-less authentication between AI services and enterprise tools.
Hands-on experience fine-tuning and prompting frontier models (GPT-4, Claude, Gemini, Llama) and a deep understanding of RAG, Transformers, Embeddings, and Tokenization.
Strong ability to build and optimize data pipelines; experience with SQL, NoSQL, and handling large-scale industrial datasets for synthetic data generation.
Familiarity with integrating GenAI solutions into business tools (e.g., PowerBI, Tableau, MS Teams, and Slack).
Must have practical experience working with chatbots that are live and actively used in production systems.
Bachelor’s or Master’s degree in Computer Science, Data Science, AI Engineering or a related quantitative field.