AI Architect

ReKnew Overview

We are ReKnew! Our mission is to help Enterprises revitalize their core business and organization by positioning themselves for the new world of AI. ReKnew is a startup founded by practitioners, surrounded by advisors and built on decades of experience in Enterprise technology, data, analytics, AI, digital and automation across industries. We are looking for top talent to join us in this mission.

Description / What You’ll Do

As a key member of our team, you’ll architect AI-powered solutions that transform how our clients operate. Your focus will be building intelligent agentic solutions that enhance sales, customer success, HR, finance, risk, and other core functions and workflows.

•      Pioneer next-generation enterprise applications by architecting scalable, interoperable AI agents that reimagine and automate workflows across sales, customer success, marketing, finance and other core functions

•      Rapidly prototype and validate Gen AI solutions through quick proof-of-concepts, then leverage learnings and feedback to ship production-ready solutions at speed

•      Design robust systems that effectively manage uncertain AI-generated results, create reliable guardrails, and develop flexible products capable of handling the inherent variability in generative AI outputs.

•      Go beyond prompt engineering and design with optimization and a bias for probabilistic inputs with deterministic outputs

•      Drive innovation by researching GenAI and Agentic AI advancements, sharing insights, and proposing new tactics, patterns and best practices that leverage emerging AI, open source or commercial capabilities.

•      Understand how various cloud (AWS, GCP, Azure) and data platforms (Snowflake, Databricks) and other prominent Enterprise technologies fit into an agentic architecture.

•      Work closely with our delivery teams to assess client use cases and design solutions.

•      Consult and contribute to the creation of the ReKnew StarterPacks accelerators.

•      Engage our engineers to ensure everyone stays ahead of the curve through hands-on exercises, lunch-and-learn type sessions and office hours.

•      Document standards, patterns and best practices and enforce them through code reviews and solution design

•      Be available to consult with clients or partners and offer input into proposals and statement of work documents.

Core Skills & Technologies

•       Strong programming skills: Proficiency in Python and/or JavaScript/TypeScript

•       NLP understanding: Knowledge of language models, embeddings, and text processing techniques

•       Context engineering: Ability to craft effective prompts, skills and MCP servers and tools that generate desired outputs

•       Fine-tuning expertise: Experience fine-tuning foundation models for specific applications

•       Data engineering: Skills to prepare, clean, and structure data for AI training

•       System design: Capability to design scalable AI systems and workflows.

Agent-Specific Skills

•       Agent architecture design: Understanding of different agent frameworks and architectures (ex: LangGraph, AWS AgentCore)

•       Tool integration: Ability to connect agents with external tools, APIs, and data sources

•       Memory systems: Knowledge of techniques for implementing context and memory

•       Planning algorithms: Familiarity with goal-setting and planning approaches

•       Multi-agent systems: Experience designing systems where multiple agents collaborate (ex: A2A)

•       Feedback mechanisms: Implementation of human and automated feedback loops

•       Evaluation frameworks: Skills to assess agent performance and behavior.

Specialized Knowledge

•       Reinforcement learning: Understanding of RLHF and related techniques

•       Retrieval-augmented generation (RAG): Experience implementing retrieval systems

•       Agentic workflows: Ability to create complex multi-step processing pipelines

•       Production deployment: Knowledge of containerization, APIs, and serving infrastructure

•       LLMOps: Skills for monitoring, updating, and managing LLM applications in production

•       Vector databases: Experience with embedding storage and similarity search.

Who You Are

•      Seasoned software engineer with proven experience building products 0-1 and a strong proficiency in Python.

•      Push engineering boundaries by chall…