Principal AI Engineer Chisinau

We fuse together exceptional talent who deliver outstanding software solutions. Our approach has helped us grow 60% in 2021, 94% in 2022, while in 2023 we joined forces with Insight, a Fortune 500 company and a leading solutions and systems integrator. With exciting growth plans and cutting-edge projects, there has never been a better time to join our incredible team. 

We fuse together exceptional talent who deliver outstanding software solutions. Our approach has helped us grow 60% in 2021, 94% in 2022, while in 2023 we joined forces with Insight, a Fortune 500 company and a leading solutions and systems integrator. With exciting growth plans and cutting-edge projects, there has never been a better time to join our incredible team.

We are establishing a AI Engineering team who will work closely with our most strategic customers to deeply understand their use cases and design, build, and implement products for them. As one of our founding AIs, you will deploy these solutions on the latest infrastructure for the world's most influential businesses, driving real business impact through the newest models and our own innovations in technical delivery.

AI Engineers' responsibilities look similar to those of a hands-on AI startup CTO: you'll work in small teams to own delivery of high stakes projects with clients. A day's work may include building LLM workflows on a large scale, interacting with customers to understand their needs and set their AI strategy, but the most impact will be driven by implementing solutions into the real world of our partner's organizations.

We are looking for customer-focused software engineers to build effective custom software that leverages leading AI models and technology to solve real customer problems. You will partner directly with customers to conceptualize, design, and implement cutting-edge AI solutions. This role focuses on leveraging generative AI models, agentic systems, and iterative prototyping to build impactful proofs of concept (PoCs) that address unique business challenges. The AI engineer acts as a bridge between advanced AI technologies and practical enterprise applications, ensuring that solutions are both innovative and actionable.

You will collaborate closely with Sales, Solutions Engineering, Solutions Architects, and Customer Success Managers who work on the same account. You will also be self driven to learn about the AI market and bring forward that knowledge to improve the way in which we deliver to customers.

Responsibilities

Customer Engagement:

Collaborate deeply with clients to understand their strategic objectives, technical requirements, and operational constraints.

Serve as a trusted advisor for AI strategy, guiding clients through the process of ideating and implementing generative and agentic AI solutions.

Facilitate workshops and brainstorming sessions to identify high-value use cases for AI technologies.

AI Solution Development:

Design, prototype, and deploy AI-powered PoCs using generative models (e.g., GPT, DALL-E) and agentic systems tailored to specific client needs.

Build end-to-end pipelines for deploying AI solutions on client infrastructure, ensuring scalability, security, and performance.

Experiment with cutting-edge methods in natural language processing (NLP), computer vision, reinforcement learning, and multi-agent systems to deliver innovative solutions.

Iterative Prototyping:

Use an experiment-driven approach to rapidly test hypotheses and refine prototypes in collaboration with client teams.

Develop reusable frameworks and tools to accelerate the deployment of generative AI solutions across diverse industries.

Cross-Functional Collaboration:

Work closely with Sales, Applied Research, Product Development, and Customer Success teams to ensure seamless project execution.

Provide actionable feedback from customer engagements to inform the development of new AI capabilities.

Knowledge Sharing:

Document best practices and lessons learned from client projects to contribute to internal knowledge bases.

Mentor junior engineers on the application of generative and agentic AI technologies in real-world scenarios.

Requirements

Technical Expertise:

Strong proficiency in programming languages such as Python or JavaScript, with experience in frameworks like TensorFlow or PyTorch.

Hands-on experience with generative AI models (e.g., GPT-4/5), agentic systems, or reinforcement learning frameworks.

Familiarity with deploying machine learning models in production environments using cloud platforms (e.g., AWS, Azure) or on-premise systems.

Problem-Solving Ability:

Proven ability to translate abstract business challenges into concrete technical solutions using generative AI.

Strong analytical skills to evaluate model performance and optimize for specific use cases.

Client-Facing Skills:

Exceptional communication skills for explaining complex AI concepts to diverse stakeholders.

Ability to build trust-based relationships with clients and navigate ambiguous problem domains collaboratively.

Adaptability:

Flexibility to work across industries such as healthcare, finance, defense, or retail while tailoring solutions to each domain.

Willingness to travel or work on-site with clients as required.

Requirements (Education, Certification, Training, and Experience)

Bachelor's degree in computer science or related field or equivalent experience

At least 3 years of experience in software engineering or applied machine learning roles.

Direct experience working with customers on the development of AI-driven applications is highly desirable

Passion for exploring the frontiers of generative and agentic AI technologies.

Entrepreneurial mindset with a focus on delivering measurable business impact through innovative solutions.

Commitment to continuous learning and staying at the forefront of AI advancements.

This role is ideal for those who thrive at the intersection of technology innovation and customer engagement. You will have the opportunity to shape the future of enterprise AI adoption while solving some of the most complex challenges faced by leading organizations.

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