Associate Director

Role: To deliver faster, smarter, and better business outcomes for our clients & partners, powered by AI.

What are we looking for?

1. This entrepreneurial technology leadership position challenges the client status quo by helping them re-imagine the art of what is possible using a consulting mindset and business strategy skills.
2. This position oversees the delivery of Applied AI Engineering and carries the Client Success & Delivery DNA.
3. This position requires a fanatic iterative improvement ability - the ability to architect a solution, code, research, code more, research more and code some more, rebuild and re-architect, you get the drift.
4. We are seeking hard-core geeks turned engineering managers turned management consultants bored of delivering 80-page PDFs. We want people who are hands-on techies and are interested in building things that matter to businesses, generating real outcomes.

What are we not looking for?

1. Mere Delegator. Non 'do-er', Budget owner. Agency manager. Co-ordinator. Program Manager.
2. Thrives in aligning people most of the time and may be great at it, but not awesome at doing things .
3. A safe player - Not used to taking bold meaningful bets every month, smartly & swiftly, with a desire to create a leveraged impact by solving differently.

Major Roles & Responsibilities

1. Develop and execute a strategic roadmap for executing Applied AI engineering projects with a product engineering mindset .
2. Lead and inspire a high-performance core group of developers, architects & engineering managers.
3. Responsible for hiring, training, coaching, team building, assessing performance, providing feedback, mentoring, and helping the team succeed. Our enthusiastic Data Scientists are just getting started and as a manager, you guide the way and set up examples by coming up with the best solutions to complex engineering problems.
4. Collaborate with architects, product management, and other engineering teams to create solutions that increase the platform's value.
5. Own Delivery - This includes overseeing the end-to-end delivery of Applied AI projects, ensuring adherence to timelines, budget, and impeccable engineering quality, setting up and managing periodic progress meeting,s and act as a point of escalation for project issues, providing timely resolution and effective communication with stakeholders.
6. Participate with senior management in developing a long-term technology road map. Influence, collaborate and communicate effectively with various leaders.
7. Drive a HAPPIER culture of constant improvement, identifying and implementing processes helping establish searce as the best-suited software engineering partner.

Education & Experience

Is Education overrated? Yes. We believe so. However there is no way to locate you otherwise. So we might look for a Bachelor's or Master's degree in engineering from a reputed institute or you should be programming from 12. And the latter is better. We will find you faster if you specify the latter in some manner along with:

1. Proven experience of 5+ years in a leadership role overseeing Applied AI engineering teams, preferably within a professional services environment.
2. Successful track record of Solution Architecting and High-end AI-based software development.
3. Strong technical background with expertise in Generative AI, Google AI APIs, Machine Learning, software development methodologies, languages, and frameworks.
4. Excellent communication skills with the ability to articulate technical concepts to both technical and non-technical audiences.
5. Demonstrated success in delivering complex software projects on time and within budget.
6. Ability to thrive in a fast-paced, dynamic environment and adapt to evolving business needs.
7. Leadership qualities include strategic thinking, decision-making, problem-solving, and team-building.
8. Experience in client-facing roles with a focus on building and maintaining relationships.
9. Our technology stack is insane, and the role requires experience and understanding of technologies like:

- Python, Pyspark, TensorFlow
- Databases: MongoDB, Google Cloud SQL, Graph/NoSQL, Bigtable
- Google App Engine, GKE, Vertex AI, Doc AI, Conversational AI

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