Co- Founder & CTO

Co\-Founder \& CTO — Neuro\-Symbolic AI, GNNs \& AGI Research

• *Company:** Siellium Global Labs Private Limited
• *Location:** Bengaluru, India (Hybrid)
• *Job Type:** Full\-time \| Co\-Founder
• *Compensation:** 100% Equity\-Based

About Siellium Global Labs

Siellium Global Labs is building advanced artificial intelligence systems focused on reasoning, generalization, adaptation, and reliable autonomous execution, with a long\-term vision toward Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI).

At the core of our work is a **Neuro\-Symbolic AI Engine** integrating neural learning, symbolic reasoning, probabilistic logic, Graph Neural Networks (GNNs), Hybrid Graph Neural Networks, structured knowledge representation, and autonomous planning.

Our research explores how neural models, logical inference, graph\-based learning, evolutionary search, and adaptive reasoning can work together to develop AI systems capable of solving complex problems, learning from experience, reasoning over evidence, and validating their decisions.

We aim to build scalable intelligence architectures that bridge statistical learning and structured reasoning while supporting explainability, reliability, and enterprise\-grade execution.

About the Role

We are seeking a technically exceptional and research\-driven **Co\-Founder \& Chief Technology Officer (CTO)** to lead the architecture, research, and development of Siellium's Neuro\-Symbolic AI Engine.

The ideal candidate will have strong expertise in AI/ML engineering, GNNs and Hybrid GNN architectures, symbolic and probabilistic reasoning, and advanced cognitive architectures. Practical knowledge of is required, alongside an understanding of **Recursive Self\-Improvement (RSI)** and the technical challenges of developing adaptive AI systems.

You will define the technical roadmap, lead foundational AI research, develop core intelligence components, build the engineering and research team, and translate ambitious research objectives into testable, working systems.

This is a hands\-on founder\-level role combining AI research, architecture design, implementation, technical leadership, and company building.

Key Responsibilities

• *1\. Neuro\-Symbolic AI Engine**

• Architect an integrated intelligence engine combining deep learning, symbolic reasoning, probabilistic inference, graph\-based learning, and structured knowledge representation.
• Develop interfaces between neural models and explicit rules, facts, relations, constraints, and reasoning procedures.
• Design mechanisms for evidence tracking, consistency checking, inference validation, and explainable decision\-making.

• *2\. Graph Neural Networks and Hybrid GNNs**

• Design, implement, and evaluate GNN architectures for relational learning, graph representation, and complex dependency modelling.
• Develop **Hybrid GNN architectures** integrating graph learning with neural\-symbolic reasoning, probabilistic logic, knowledge representations, or other structured inference mechanisms.
• Explore graph\-based reasoning, message passing, dynamic graphs, heterogeneous graphs, and learning over structured relational data.
• Evaluate scalability, generalization, robustness, and performance across relevant graph\-learning and reasoning benchmarks.

• *3\. Recursive Self\-Improvement and Adaptive Intelligence**

• Research architectures and evaluation methods for Recursive Self\-Improvement (RSI), including controlled system improvement, feedback\-driven adaptation, and iterative optimization.
• Develop mechanisms for analysing system performance, identifying weaknesses, proposing improvements, and validating changes against explicit criteria.
• Establish safeguards through reproducible evaluations, regression tests, versioning, rollback, and human approval where appropriate.
• Distinguish verified improvements from speculative claims and ensure that system modifications remain controlled and measurable.

• *4\. Reasoning, Planning and Autonomous AI**

• Build multi\-step reasoning and planning systems capable of decomposing objectives, evaluating alternatives, managing constraints, and selecting tools.
• Develop mechanisms for uncertainty assessment, contradiction detection, task\-state management, and evidence\-based decision\-making.
• Integrate AI reasoning with controlled execution, postcondition verification, error recovery, and auditable workflows.

• *5\. Research and Model Development**

• Lead experiments across LLMs, deep learning, GNNs, Hybrid GNNs, evolutionary search, reinforcement learning, and related fields.
• Develop reproducible training, testing, benchmarking, and evaluation pipelines.
• Measure reasoning accuracy, generalization, calibration, reliability, computational efficiency, and robustness.

• *6\. Engineering and Technical Leadership**

• Own system architecture, APIs, databases, distributed infrastructure, model serving, GPU optimization, and production deployment.
• Establish engineering standards covering testing, security, observability, documentation, and maintainability.
• Recruit, mentor, and lead AI researchers and engineers while aligning research priorities with product and business objectives.
• Support fundraising, technical due diligence, strategic partnerships, and customer\-facing technical discussions.

Required Qualifications

• Strong experience in AI/ML engineering, deep learning, and advanced software architecture.
• **Practical knowledge MOSES, and PLN**, including their underlying concepts, reasoning approaches, and potential integration into hybrid intelligence architectures.
• Strong understanding of **Graph Neural Networks (GNNs)** and **Hybrid GNNs**, including graph representation learning, message passing, relational reasoning, and integration with structured knowledge.
• Knowledge of symbolic AI, formal logic, probabilistic inference, knowledge representation, or cognitive architectures.
• Understanding of **Recursive Self\-Improvement (RSI)**, adaptive systems, iterative optimization, and the evaluation and safety challenges associated with self\-modifying or self\-improving AI.
• Experience with LLMs, AI research, model development, evaluation, or autonomous agent systems.
• Strong software engineering, system design, testing, debugging, and performance\-optimization skills.
• Familiarity with distributed systems, databases, cloud infrastructure, and production AI deployment.
• Strong analytical and research capabilities, with a commitment to experimental rigor and measurable results.
• Entrepreneurial mindset, technical ownership, and readiness to build an AI company from an early stage.

A Master's or PhD in Computer Science, Artificial Intelligence, Mathematics, or a related field is preferred. Demonstrable research, relevant implementations, substantial open\-source contributions, or equivalent industry experience may substitute.

Equity\-Based Co\-Founder Opportunity

• *This is a 100% equity\-based position.**

The successful candidate will join as a technical co\-founder, with equity participation intended to align long\-term ownership with the company's development and growth.

Equity allocation, vesting arrangements, founder responsibilities, decision\-making rights, intellectual property obligations, and other relevant terms will be discussed and documented through mutually agreed formal agreements.

This opportunity is intended for someone willing to make a meaningful long\-term commitment to foundational AI research, technical leadership, and company building.

What We Expect

We value deep technical expertise, intellectual honesty, independent thinking, reproducible research, and the ability to transform theoretical concepts into functioning systems. Candidates should be comfortable challenging assumptions, evaluating competing architectures, and demonstrating progress through measurable experiments rather than unsupported claims.

How to Apply

Please share your CV or LinkedIn profile, relevant AI research or implementations, GitHub repositories or publications, and a brief description of your experience with neuro\-symbolic AI, GNNs/Hybrid GNNs, MOSES, PLN, or RSI\-related research.

e\-Mail \- ash.m@siellium.com

• *Applicants must acknowledge that this is an equity based co\-founder position**

Join Siellium Global Labs to help build the next generation of reasoning\-driven, graph\-integrated, adaptive, and autonomous AI systems.

Pay: ₹100,000\.00 \- ₹500,000\.00 per year

Work Location: Remote