Provectus

Provectus

Provectus provides consulting services in artificial intelligence and machine learning, assisting businesses in integrating AI solutions to meet their unique objectives and enhance their operational capabilities across various industries.

Professional Services
251-1K
Founded 2010

Description

  • Define product vision and roadmaps for client solutions using GenAI, LLMs, RAG architectures, and Agentic AI frameworks.
  • Lead the end-to-end product lifecycle for AI and ML products from ideation through launch.
  • Develop business cases by analyzing market opportunities and ROI for AI implementations.
  • Oversee product strategy for large-scale data migration projects across AWS, Azure, and GCP.
  • Guide data product development including ingestion pipelines, transformation layers, governance frameworks, and consumption APIs.
  • Ensure data quality, security, compliance, and observability across deliverables.
  • Facilitate Agile ceremonies and maintain well-groomed backlogs with detailed feature and epic-level stories.
  • Work with engineering teams to decompose complex features into incremental releases with clear technical dependencies.
  • Partner with client stakeholders, engineering teams, data architects, and ML engineers to deliver integrated solutions.
  • Conduct design thinking workshops and user research sessions to validate product direction.

Requirements

  • Bachelor's degree in Technology or a business-related field; Master's degree preferred.
  • 5-7+ years of experience in technical product management, solutions architecture, or software engineering.
  • 5+ years of product management experience with end-to-end product ownership.
  • 3-5+ years of experience with AI/ML products, Generative AI, or data platform development.
  • 3-5+ years of experience working in Agile/Scrum environments with strong command of Agile methodologies and ceremonies.
  • Deep understanding of cloud architectures across AWS, Azure, and GCP.
  • Experience with LLM integration, prompt engineering, RAG architectures, fine-tuning, and Agentic AI frameworks such as LangChain, LlamaIndex, or AutoGen.
  • Experience with ETL/ELT patterns, data modeling, Snowflake, Databricks, dbt, Airflow, and Kafka/streaming architectures.
  • Experience with cloud AI and data services such as AWS SageMaker and Bedrock, Azure OpenAI Service and Synapse, or GCP Vertex AI and BigQuery.
  • Experience with MLOps practices including model deployment, monitoring, versioning, CI/CD for ML, feature stores, and experiment tracking.
  • Knowledge of data migration assessment methods, migration patterns, data validation, and cutover strategies.
  • Experience with API design, microservices, containerization, and CI/CD pipelines.
  • Solution design and technical architecture capabilities.
  • Ability to translate business needs into technical specifications and manage stakeholders across technical and non-technical audiences.
  • Strong analytical thinking, problem-solving, communication, risk identification, dependency mapping, and mitigation planning.
  • Nice to have: 3+ years of software development or data engineering experience.
  • Nice to have: Background in consulting or professional services delivering client solutions.
  • Nice to have certifications: AWS Solutions Architect, Azure Data Engineer, GCP Professional Data Engineer, or Certified Scrum Product Owner.

Benefits

  • Long-term B2B collaboration.
  • Fully remote work setup.
  • Budget for medical insurance.
  • Paid sick leave, vacation, and public holidays.
  • Continuous learning support, including unlimited AWS certification sponsorship.

Interested in this position?

Apply directly on the company website

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