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Product Architect

Job in Hartford, Hartford County, Connecticut, 06112, USA
Listing for: Jobs via Dice
Full Time position
Listed on 2026-02-15
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Job Title:

Product Architect

Location:

Hartford, Connecticut (On-site)

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Flexon Technologies Inc., is seeking the following. Apply via Dice today!

Job Description

Lead the end-to-end AI architecture for enterprise products on Google Cloud Platform (Google Cloud Platform), spanning Generative AI, Agentic AI solutions, classical ML/DL, and scalable microservices. Define reference architectures, oversee the model and pipeline lifecycle, and guide engineering squads across Python and Java stacks to industrialize LLMs, Lang Graph agent workflows, and secure, reliable AI platforms. Design and implement GenAI and Agentic AI solutions, including LLMs, prompt strategies, tool use, and grounding techniques.

Build Lang Graph (or Lang Chain) agent workflows for multi-step planning, orchestration, and safe execution flows. Develop ML/DL solutions including supervised and unsupervised learning, NLP, vector search, RAG, embeddings, and model evaluation using Tensor Flow and PyTorch. Architect and deploy solutions on Google Cloud Platform services including Vertex AI (training, endpoints, evaluation), Big Query, Dataflow/Beam, Pub/Sub, Cloud Storage, IAM, KMS, and networking.

Develop production-grade applications using Python (frameworks, packaging, testing) and Java (Spring Boot services exposing model APIs). Apply performance, reliability, and scalability best practices across services and platforms. Establish and manage MLOps and LLMOps practices, including model versioning and registries, CI/CD pipelines, feature and vector stores, telemetry and monitoring, quality gates, red‑teaming and risk evaluation. Collaborate with offshore and cross‑functional teams to deliver AI/ML solutions ure security and compliance standards, including PII/PHI controls, encryption in transit and at rest, data retention policies, and governance and audit readiness.

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