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Enterpret

AI Tech Lead Manager

Reposted 17 Days Ago
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In-Office
Bengaluru, Karnataka
Senior level
Easy Apply
In-Office
Bengaluru, Karnataka
Senior level
Lead AI research and innovation, mentor a team, collaborate cross-functionally, drive customer-centric solutions, and promote rapid experimentation.
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About Enterpret

Enterpret is at the forefront of AI-native applications, unlocking the power of customer feedback for businesses. We centralize feedback from various sources, providing actionable insights to drive customer-centric decisions. Our customers include leading companies like Canva, Descript, and Notion. Backed by top-tier investors like Kleiner Perkins and Sequoia India, we are committed to transforming how businesses understand and act on customer feedback.

Read more about our team, core values, and operating principles - here.

Role Overview

As the Technical Lead Manager (Applied AI Engineering) at Enterpret, you will act as a principal investigator, bridging advanced AI research and practical applications. This role emphasizes strong research capabilities and is ideal for someone eager to step into a leadership position while continuing hands-on work with cutting-edge AI technologies. You will lead a team of talented engineers and researchers, tackling complex problems and driving innovation in customer feedback analysis.

Key Responsibilities
  1. Lead Advanced AI Research and Innovation
    • Serve as the primary point of contact for challenging technical problems.
    • Conduct in-depth research to develop innovative AI solutions.
    • Run Proof-of-Concept (POC) projects to explore new technologies and validate approaches.
    • Own the cost of serving models.
  2. Collaborate with Cross-Functional Teams
    • Interface with product and engineering teams to align AI initiatives with business objectives.
    • Translate complex product requirements into actionable technical tasks.
    • Ensure seamless integration of AI solutions into existing products.
    • Ensure timely delivery of projects.
  3. Mentor and Guide the AI Team
    • Break down complex problems into manageable tasks for team members.
    • Provide guidance and mentorship, fostering a culture of excellence and continuous learning.
    • Encourage autonomy within the team, minimizing the need for handholding.
  4. Drive Rapid Experimentation and Iteration
    • Establish processes that promote quick iterations and experimentation.
    • Foster an environment where innovative ideas are tested, learned from, and iterated upon swiftly.
  5. Champion Customer-Centric Solutions
    • Embed a customer-first mindset in all AI initiatives.
    • Collaborate with customer success teams to gather insights and tailor solutions to real customer needs.

About You
  • Research Expertise: Strong background in AI research with a passion for applying advanced techniques to solve real-world problems. Experience handling the annotation team is a bonus.
  • Leadership Ambition: Ready to step into a leadership role while maintaining hands-on involvement in research and development.
  • Problem Solver: Ability to tackle complex technical challenges and develop innovative solutions.
  • Collaborative Mindset: Excellent communication skills, humble attitude and ability to work cross-functionally with product and engineering teams.
  • Startup Experience: Thrives in dynamic, fast-paced environments, preferably with experience in early-stage startups.
  • LLM Expertise: Proven track record of building and shipping successful applications powered by Large Language Models.
  • Customer-Centric Approach: Strong commitment to understanding and addressing customer needs through AI-driven solutions.
Benefits and Perks
  • Autonomy and Ownership: Influence and shape the future of an early-stage startup.
  • Competitive Compensation: Highly competitive salary and early-stage startup equity.
  • Cab to and from Office, Food at Office: Enterpret sponsors travel to and from the office and provide meals so you can focus on doing your best work.


Top Skills

AI
Ai Research
Engineering Collaboration
Large Language Models

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