Description :

Experience : 7+ Years

Company : Searce (AI-native modern tech consultancy)

Role Type : Directly Responsible Individual (DRI) / Hands-on Technical Lead

Role Summary :

Searce is looking for a Manager of AI Engineering who is a "Happier-at-heart" leader and a principal technical expert. This is not a traditional management role; you are the Directly Responsible Individual (DRI) for your AI squad, expected to lead by impact and example, not by control. You will bridge the gap between ambitious AI concepts and production-grade realities by designing, coding, and deploying scalable intelligent systems. Operating with an "Always Beta" mindset, you will own the entire lifecycle of high-impact client initiativesfrom initial ideation and proof-of-concept to global deployment and MLOps optimization. You will thrive in an engineering-led consultancy environment where math, tech, and first-principles thinking drive business reinvention and lasting competitive advantage.

Responsibilities :

- Engineering & Full-Lifecycle Deployment : Act as a hands-on builder for core technical components, executing the design, coding, and deployment of robust, scalable AI/ML solutions.

- System Architecture & MLOps : Directly build and oversee high-performance AI architectures, ensuring they are production-ready, secure, and maintainable for long-term operational success.

- Squad Delivery Ownership : Own technical outcomes from ideation to deployment with precision, ensuring that the squads contributions deliver tangible, real-world business value.

- Mentorship through Action : Coach and develop a high-performing squad of "Do-ers," fostering a culture of continuous innovation and technical excellence through clarity of code and data insights.

- Technical Integration : Partner with Solutions Consultants and Data Scientists to translate chaotic business challenges into precise technical requirements and seamless integrations.

- Responsible AI Governance : Embed fairness, transparency, and privacy considerations into every line of code and model architecture from the ground up.

- Scalability Optimization : Constantly refine and optimize core system components to ensure reliability and future extensibility across multi-modal AI systems.

- Stakeholder Influence : Steer decision-making through logical arguments, robust data insights, and the demonstrated impact of technical delivery.

Technical Requirements (Tech Superpowers) :

- AI Engineering Mastery : 7+ years of experience building and scaling end-to-end AI solutions, including deep expertise in foundational models and custom AI architectures.

- Google Cloud Ecosystem : Expert proficiency in Google Cloud Platform (GCP), specifically Vertex AI, BigQuery ML, and GKE for large-scale MLOps.

- Intelligent Architecture : Proven ability to translate abstract requirements into scalable, production-grade AI platforms and complex multi-modal systems.

- Cloud-Native Capability : Deeply capable of leveraging cloud-native AI/ML ecosystems to manage and deploy high-performance intelligent agents.

- Core Engineering : Strong hands-on coding skills in Python/Go/Java with a deep understanding of training methodologies and model optimization.

- Education : BE/BTech in CS/Engineering; an MS in CS/Engineering and Google Cloud Professional certifications are highly preferred.

The DNA of a Searcian (Soft Skills) :

- Founder Mindset : Thinks like a founder and acts like an owner; views setbacks as opportunities for learning.

- Truth over Comfort : Believes in ideas over titles and embraces honest, transparent communication to solve engineering challenges.

- Structured Problem Solving : Ability to simplify chaotic technical hurdles using first-principles thinking and logical decomposition.

- Happier-in-Action : Demonstrates an adaptable, positive, and excellence-minded attitude in every client interaction and team decision.

- Chaos Navigator : Remains calm in high-pressure situations, evolving faster than the market to maintain a competitive edge.