Addepto
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Addepto is a leading AI consulting (https://addepto.com/ai-consulting/) and data engineering (https://addepto.com/data-engineering-services/) company that builds scalable, ROI-focused AI solutions for some of the world’s largest enterprises and pioneering startups, including Rolls Royce, Continental, Porsche, ABB, and WGU. With an exclusive focus on Artificial Intelligence and Big Data, Addepto helps organizations unlock the full potential of their data through systems designed for measurable business impact and long-term growth.
The company’s work extends beyond client engagements. Drawing from real-world challenges and insights, Addepto has developed its own product – ContextClue – and actively contributes open-source solutions to the AI community. This commitment to transforming practical experience into scalable innovation has earned Addepto recognition by Forbes as one of the top 10 AI consulting companies worldwide.
As part of KMS Technology, a US-based global technology group, Addepto combines deep AI specialization with enterprise-scale delivery capabilities—enabling the partnership to move clients from AI experimentation to production impact, securely and at scale.
We are looking for a Pre-Sales Engineer to help clients unlock the value of modern AI and data platforms. In this role, you will support organizations in the early stages of their transformation by aligning technical solutions - such as machine learning, LLM-based applications, and cloud data platforms - with their strategic business goals.
You will become an expert in our consulting offerings across AI/ML, LLM integrations, and modern data engineering solutions, acting as a trusted technical advisor during pre-sales engagements. Working closely with sales, delivery, and engineering teams, you will help shape solution concepts, support technical discovery, and ensure a smooth transition from early discussions to project implementation.
Serve as a technical advisor during pre-sales and early engagement stages, helping clients understand what’s possible with AI/LLMs and modern data platforms, and how these capabilities align with their strategic business goals.
Lead or support technical discovery sessions, clarifying business problems, identifying solution patterns, and assessing feasibility across both AI/ML and data platform initiatives.
Design and communicate solution architectures, including LLM integrations, AI/ML solution designs, retrieval-augmented generation (RAG), vector databases, orchestration pipelines, and data flows, as well as modern cloud data architectures such as data lakes, data warehouses, and big data processing solutions.
Create and deliver technical PoCs and PoVs, demo narratives, and early prototypes to support proposals and shape delivery, including solutions leveraging AI/ML as well as modern data engineering and analytics platforms.
Contribute to internal R&D by evaluating emerging AI tools, libraries, frameworks, and modern data technologies (e.g., cloud-native data platforms, data engineering tools), and translating insights into recommendations for internal teams and clients.
Collaborate with sales, delivery, and engineering teams to ensure a smooth transition from pre-sales, through technical scoping and solution design, to hand-off to delivery teams and full implementation.
Undergraduate degree or higher in Computer Science, Data Science, Engineering, or related field - or equivalent hands-on experience.
Proven experience in technical roles - e.g., exposure to AI/ML products, data platforms, consulting services, solution engineering, or cloud architecture.
Foundational understanding of public cloud platforms (AWS, Azure, GCP) with experience deploying cloud-based AI solutions and/or modern data platform architectures.
Comfortable working across multiple clients and projects, often in parallel, with strong organizational and time management skills.
A strong foundational understanding of AI/ML workflows - from data preprocessing and model training to evaluation and deployment.
Familiarity with LLM-based applications, including embeddings, vector databases, and orchestration frameworks (e.g., LangChain, LlamaIndex).
Working knowledge of MLOps and orchestration tools like MLflow, Airflow, Kubeflow, Vertex AI, or SageMaker.
Proficiency in Python and experience with common AI/ML libraries such as pandas, scikit-learn, PyTorch, or TensorFlow.
Understanding of modern data architectures and data engineering concepts, including ETL/ELT pipelines, big data processing, and cloud data services (e.g., Azure Data Factory, Azure Synapse, Databricks, or similar platforms).
Strong communication skills, with the ability to simplify complex concepts for diverse audiences, including AI engineers, data scientists, data engineers, and non-technical stakeholders.
Excellent time management and multitasking ability - comfortable working across several customer projects and internal teams.
Exposure to or interest in sales processes, technical demos, and customer-facing engagements.
Work in the rapidly evolving world of AI & Big Data.
Engage with top-tier global enterprises and cutting-edge startups on international projects.
Enjoy flexible work arrangements, allowing you to work remotely or from modern offices and coworking spaces.
Accelerate your professional growth through career paths, knowledge-sharing initiatives, language classes, and sponsored training or conferences.
Choose your preferred form of cooperation: B2B or a contract of mandate, and enjoy 20 fully paid days off.
Participate in team-building events and utilize the integration budget.
Celebrate work anniversaries, birthdays, and milestones.
Access medical and sports packages, eye care, and well-being support services, including psychotherapy and coaching.
Get full work equipment for optimal productivity, including a laptop and other necessary devices.
With our backing, you can boostyourpersonal brand by speaking at conferences, writing for our blog, or participating in meetups.
Experience a smooth onboarding with a dedicated buddy, and start your journey in our friendly, supportive, and autonomous culture.
Originally posted on Himalayas