Provectus

Solutions Engineer

• Lead pre-sales technical discussions with clients;
• Design ML architectures to solve complex business problems;
• Ensure solutions are scalable and aligned with client needs;
• Architect agentic AI solutions leveraging LLMs;
• Evaluate agent frameworks for client use cases;
• Support delivery teams and mentor engineers during project execution.

ML Solutions Architect

Artificial Intelligence

• Owns the curriculum that makes the shift to AI successful
• Facilitates executive coaching sessions
• Builds connections with customers to surface use case candidates
• Contributes to the Provectus enablement playbook

AI Enablement

Machine Learning Engineer

• Create ML models from scratch or improve existing models.
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap.
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

Senior ML Engineer, LLMs, AWS

Backend Engineer

• Maintain, improve, and extend an AI platform already running in production
• Handle a mix of backend development, data engineering, DevOps, and infrastructure work
• Translate business and product requirements into technical decisions independently
• Work directly with internal stakeholders and consumer teams
• Establish and maintain engineering best practices for the platform
• Identify and resolve technical issues as the first line of defense

Senior Engineer – Generalist, Python, Data

Business Development Rep

• Source and qualify new business opportunities in North America
• Build and manage a client pipeline across multiple verticals
• Proactively reach out to prospects via outbound (email, calls, social)
• Coordinate discovery & qualification conversations
• Partner with Sales leadership to close deals
• Attend industry events, conferences, and client meetings (travel expected 30% of the time)

Business Development Manager – AI/Cloud Solutions on AWS, FinTech, Insurance, Healthcare, LifeSciences

• Source and qualify new business opportunities in North America.
• Build and manage a client pipeline across multiple verticals.
• Proactively reach out to prospects via outbound (email, calls, social).
• Coordinate discovery & qualification conversations.
• Partner with Sales leadership to close deals.
• Attend industry events, conferences, and client meetings (travel expected 30% of the time).

Business Development Manager – AI/Cloud Solutions – FinTech, Insurance, Healthcare, Life Sciences

• Drive AI-Powered Product Innovation
• Define product vision and roadmaps for client solutions leveraging GenAI, LLMs (GPT-4, Claude, Llama, Gemini), RAG architectures, and Agentic AI frameworks
• Lead end-to-end product lifecycle from ideation through launch for AI/ML products, ensuring alignment with client business objectives and KPIs
• Develop compelling business cases by analyzing market opportunities, competitive positioning, and ROI projections for AI implementations
• Lead Complex Data & Migration Initiatives
• Oversee product strategy for large-scale data migration projects across cloud platforms (AWS, Azure, GCP)
• Guide data product development including ingestion pipelines, transformation layers, governance frameworks, and consumption APIs
• Ensure data quality, security, compliance, and observability across all deliverables
• Champion Agile Delivery Excellence
• Facilitate Agile ceremonies and maintain well-groomed backlogs with properly sized, technically detailed features and epics
• Define sprint goals aligned with quarterly objectives and long-term product vision
• Balance technical debt management with feature delivery, advocating for architectural improvements
• Enable Cross-Functional Collaboration
• Partner with client stakeholders, engineering teams, data architects, ML engineers, and UX designers to deliver integrated solutions
• Translate technical capabilities into business value narratives tailored for different audiences, from developers to executive leadership
• Conduct design thinking workshops, user research sessions, and gap analyses to uncover insights and validate product direction.

Senior Solution Owner – AI & Data Solutions

Business Development Manager – AI/Cloud Solutions, AWS, FinTech, Insurance, Healthcare, Life Sciences

Business Development Manager – AI/Cloud Solutions, AWS – FinTech, Insurance, Healthcare, Life Sciences

• Build and optimize RESTful APIs and servers using frameworks such as FastAPI, Django REST, or Flask.
• Implement and optimize Retrieval Augmented Generation (RAG) systems;
• Profile and optimize Python code to enhance performance;
• Collaborate with cross-functional teams, including ML engineers and product managers, to deliver high-quality products;
• Write clean, maintainable, and well-documented code;
• Stay updated with the latest developments in Python and AI technologies and propose innovative solutions.

Senior Python Engineer, GenAI & LLM Orchestration

DevOps Engineer

• Manage and improve CDN configuration including caching rules, redirects, and traffic routing across a globally distributed edge
• Triage CDN related production issues through log analysis and performance investigations for high traffic events
• Review merge requests from product and platform engineering teams and advise on cache behavior and edge performance
• Build and maintain CI CD pipelines in GitLab CI for safely delivering CDN configuration changes
• Partner with development teams across US and EU time zones to onboard new services behind the CDN
• Maintain documentation, runbooks, and operational procedures while contributing to monitoring and alerting on edge traffic

Middle Site Reliability Engineer – CDN, DevOps

AI Engineer

Senior Generalist Engineer – Healthcare AI Platform

• Design and build cloud-native data, LLM-based, and agentic AI solutions addressing real client business challenges
• Implement and optimize RAG systems for production use cases
• Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.
• Support presales: discovery calls, technical proposals, scoping, and client-facing demos
• Own the technical direction of client engagements from discovery through delivery — the go-to authority for clients and the internal team
• Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs
• Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.
• Deploy ML and LLM-based solutions
• Implement MLOps, LLMOps, and AgentOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.
• Lead architecture reviews, produce technical design documents, and contribute to standards
• Mentor engineers, lead code reviews, and share knowledge across the team.