
Techmatters - AI Engineering Manager
1 week ago
Description
About the Role :
Were hiring an engineer who blends large-language-model know-how, data-platform chops, and product sense. You will architect the AI stack from ingestion pipelines through model deployment, standup a credit-aware inference platform, and integrate language models into both customer-facing features and internal tools.
Key Responsibilities
- Own the AI roadmap translate business priorities into model, data, and infrastructure milestones.
- Build data & ML infrastructure design data lake, feature store, vector search (pgvector), model registry, and CI/CD for ML.
- Develop and deploy models train or fine-tune models the domain data; serve them behind low-latency, cost-controlled APIs.
- Ensure quality, cost, and compliance set up automated evaluation, token-spend monitoring, and GDPR-safe data flows.
Skills And Qualifications
- 6 to 10 years in back-end or full-stack engineering with at least one Gen-AI product or workflow in production.
- Strong in Java and fluent in Python or Node for ML tooling.
- Practical experience with LLMs, embeddings, vector search, and retrieval-augmented generation.
- Deep familiarity with AWS or GCP services, container orchestration, CI/CD, and monitoring.
- Comfortable setting up data models and MLOps processes (model registry, drift alerts, blue-green model deploys).
- Proven leadership in code reviews, technical mentoring, and cross-functional communication
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