I am an Applied AI Engineer with 4+ years of experience designing and deploying production-grade AI systems that improve efficiency and accelerate decision-making. I specialize in multi-agent systems (MAS), RAG pipelines, and scalable backend architectures, with a proven track record of reducing research synthesis and strategic analysis from days to minutes, and processing over 1M+ records for large-scale semantic search and analytics. I bring a total of 13 years of professional experience across quantitative analysis, operations, and engineering, applying systems-level thinking to deliver reliable, cost-efficient AI solutions for real-world business challenges. I enjoy translating user needs into robust system designs and collaborating with open-source communities to improve cross-environment stability.…

Elik Plim Kudowor

I am an Applied AI Engineer with 4+ years of experience designing and deploying production-grade AI systems that improve efficiency and accelerate decision-making. I specialize in multi-agent systems (MAS), RAG pipelines, and scalable backend architectures, with a proven track record of reducing research synthesis and strategic analysis from days to minutes, and processing over 1M+ records for large-scale semantic search and analytics. I bring a total of 13 years of professional experience across quantitative analysis, operations, and engineering, applying systems-level thinking to deliver reliable, cost-efficient AI solutions for real-world business challenges. I enjoy translating user needs into robust system designs and collaborating with open-source communities to improve cross-environment stability.…

Available to hire

I am an Applied AI Engineer with 4+ years of experience designing and deploying production-grade AI systems that improve efficiency and accelerate decision-making. I specialize in multi-agent systems (MAS), RAG pipelines, and scalable backend architectures, with a proven track record of reducing research synthesis and strategic analysis from days to minutes, and processing over 1M+ records for large-scale semantic search and analytics.

I bring a total of 13 years of professional experience across quantitative analysis, operations, and engineering, applying systems-level thinking to deliver reliable, cost-efficient AI solutions for real-world business challenges. I enjoy translating user needs into robust system designs and collaborating with open-source communities to improve cross-environment stability.

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Language

English
Fluent

Work Experience

Lead AI Systems Engineer at Project Mirror
January 1, 2026 - Present
Designed and deployed an AI workflow automation system to orchestrate knowledge workflows using multi-agent orchestration and heterogeneous model routing, reducing workflow times and improving reliability. Built production-ready pipelines with Gemini, Llama, Qwen models; implemented structured outputs and adversarial validation loops to cut hallucinations; enabled privacy-conscious personalization via hashed sessions; established observability tooling; enabled API integrations and scheduling features.
Lead AI Systems Engineer at Kognia AI
November 2, 2025 - December 2, 2025
Led hierarchical multi-agent system for automated research and strategy workflows; created specialized agent pipelines (research → analysis → synthesis → summarization); built asynchronous FastAPI backend; processed 1M+ records for semantic indexing; implemented role-based architecture (Market Intelligence, SWOT, Report Generation, Simulation); introduced persona simulations and structured output enforcement with adversarial validation.
Quantitative Analyst & Trader at Self-Managed Capital
January 1, 2017 - January 1, 2021
Applied quantitative analysis and probabilistic modeling to manage risk and identify market opportunities; developed systematic decision-making frameworks now applied to AI system evaluation and reliability engineering.
Accounting Assistant at Western Global Technology Co. Ltd.
January 1, 2013 - January 1, 2017
Analyzed financial workflows and identified inefficiencies, contributing to process improvements that increased operational efficiency by 15%.

Education

Bachelor of Arts in Anthropology and Geography at University of Cape Coast, Ghana
August 1, 2014 - June 1, 2018

Qualifications

AI Agents Intensive
November 1, 2025 - November 30, 2025
Generative AI Intensive
October 1, 2025 - October 31, 2025

Industry Experience

Software & Internet, Professional Services, Education, Media & Entertainment
    paper Project Mirror: Multi-Agent AI System for Workflow Automation

    Project Mirror — Multi-Agent AI System for Workflow Automation

    Project Mirror is a multi-agent AI system designed to act as a professional assistant, automating tasks such as information retrieval, scheduling, and technical reasoning through coordinated agent workflows.

    The system is built to demonstrate how AI can move beyond isolated capabilities into reliable, task-oriented tools used in real workflows, where outputs directly influence decisions and actions.

    Key Contributions:

    • Designed a hierarchical multi-agent architecture for task decomposition and execution
    • Implemented retrieval-augmented reasoning (RAG) with strict context isolation to improve accuracy
    • Integrated external tools (e.g., scheduling APIs) for real-world task execution
    • Improved system reliability through structured outputs and multi-layer validation
    • Built observability mechanisms to track system performance and debug agent behavior

    Impact:

    • Reduced complex workflow execution time from hours to minutes
    • Significantly improved output reliability through validation and adversarial testing
    • Demonstrated a scalable approach to building production-oriented AI systems

    Tech: Python, FastAPI, Google ADK, MCP, Weaviate, LLM APIs (Gemini, Llama), Docker

    paper Kognia AI

    Developed Kognia AI, a sophisticated multi-agent system designed to eliminate the “Cognitive Bottleneck” in brand strategy. Kognia moves beyond simple chatbots by deploying a specialized team of autonomous agents that collaborate to transform raw market data into high-stakes strategic insights.

    Key Technical Highlights:

    • Architecture: Implemented a Hierarchical Orchestration Pattern using the Google Agent Development Kit (ADK) to prevent context window overload and minimize hallucinations.
    • Orchestration: Engineered the kognia_nexus_agent to act as a central project manager, dynamically routing tasks to specialist agents based on user intent.
    • Grounding & Accuracy: Integrated Google Search Grounding and deep scraping tools to ensure all strategic outputs are based on real-time market facts rather than static training data.
    • Synthetic Focus Groups: Developed a Conversation Simulator Agent that allows users to “interview” data by roleplaying as specific consumer personas, providing a novel way to stress-test brand messaging.

    The Specialist Agent Team:

    • Market Intel Analyst: Automates deep-web research and trend discovery.
    • SWOT Evaluator: Applies rigid SWOT frameworks to identify opportunities and threats.
    • Report Architect & Executive Briefer: Synthesizes complex multi-agent outputs into client-ready documents and high-impact leadership summaries.

    Impact:

    • Reduced time taking for manual research and strategic insight generation from days to < 5 minutes.

    Tech Stack:
    Python | Google Gemini | Google ADK | Google Search Grounding | Generative AI | Multi-Agent Systems (MAS)