[Remote] GenAI Architect (Growth Leader)
Note: The job is a remote job and is open to candidates in USA. Tredence Inc. is seeking a hands-on AI Growth Leader with deep technical expertise in designing, building, and scaling GenAI and agentic AI systems. The role focuses on architecture, engineering execution, and innovation, owning the end-to-end lifecycle of intelligent systems and driving real-world impact across automation, decision intelligence, and customer experience.
Responsibilities
- Design and implement end-to-end GenAI systems, including: Multi-agent architectures (planner-executor models, autonomous agents) RAG pipelines and knowledge-grounded AI systems Tool-augmented LLM workflows (function calling, API orchestration) Build production-ready AI solutions, not just prototypes, ensuring scalability, reliability, and observability. Develop reusable frameworks, accelerators, and reference architectures for enterprise AI adoption
- Architect and deploy agentic AI solutions with: Memory, reasoning, task decomposition, and self-improvement loops Multi-agent collaboration and orchestration patterns Workflow automation using LLM-driven decision engines Experiment with advanced paradigms such as: Reflection and planning agents Retrieval + reasoning hybrid systems Autonomous pipelines for analytics and operations
- Work hands-on with: Frameworks: LangChain, LlamaIndex, Semantic Kernel, AutoGen, CrewAI Models: OpenAI, Claude, open-source LLMs (Llama, Mistral, etc.) Vector DBs: Pinecone, Weaviate, FAISS, Azure AI Search Build and optimize: Prompt engineering strategies Fine-tuning and adaptation (LoRA, PEFT where applicable) Latency, cost, and inference optimization Implement evaluation pipelines (hallucination detection, grounding accuracy, guardrails)
- Architect and deploy solutions on: Azure OpenAI, AWS Bedrock, Google Vertex AI Build scalable pipelines using: Kubernetes, serverless architectures, API gateways Data pipelines (Airflow, Kubeflow, Spark where needed) Ensure MLOps / LLMOps practices, including: CI/CD for AI systems Model/version lifecycle management Monitoring and feedback loops
- Build POCs, MVPs, and experimental systems rapidly to validate new ideas. Translate ambiguous business problems into working AI solutions quickly. Stay at the cutting edge of: Multimodal AI AI agents and orchestration frameworks Edge AI and lightweight deployments
- Partner with engineering, product, and business teams to translate requirements into robust AI systems. Provide hands-on mentorship to engineers and architects. Drive engineering best practices and AI architectural standards across teams
- Occasionally engage with stakeholders to: Shape use cases and validate architecture Demo working systems and prototypes Focus on showing real implementations rather than presentations
Skills
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field
- 10+ years in software engineering / solution architecture
- 5+ years of hands-on AI/ML and GenAI development
- Proven track record of building and deploying AI systems into production
- Developing LLM-based or agentic applications
- Strong experience in coding-heavy roles (not just design/presales)
- Strong programming expertise in Python (mandatory)
- Deep understanding of LLM architectures and limitations
- RAG, embeddings, vector search
- Agent frameworks and orchestration models
- Experience with APIs, microservices, distributed systems
- Docker, Kubernetes, CI/CD pipelines
- Familiarity with security, governance, and AI safety practices
- Cost-performance tradeoffs in large-scale AI systems
- Builder mindset with a passion for hands-on problem solving
- Ability to work in ambiguous, fast-evolving AI environments
- Strong communication skills to explain complex systems simply
- Curiosity and continuous learning attitude
- Contributions to open-source AI projects or research
- Experience with multi-agent systems and autonomous pipelines
- Exposure to industry applications (finance, healthcare, retail, etc.)
- Publications, patents, or thought leadership in AI/GenAI
- Experience optimizing AI systems for scale, latency, and cost
Company Overview
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