Skit.ai is hiring for Product Analyst – AI Engineering at Bangalore

Company: Skit.ai

Role: Product Analyst – AI Engineering

Location: Bangalore, Karnataka, India (100% On‑site)

Experience Required: 3 – 6 Years

Shift: 1:00 PM – 10:00 PM IST

Posted on: 18th December 2025

Apply for Product Analyst – AI Engineering

📌 Job Description

Skit.ai is looking for a Product Analyst – AI Engineering to support its Conversational AI product strategy. The role involves driving excellence in prompt engineering, analyzing performance data from voice bots, and establishing a Center of Excellence (CoE) to standardize AI practices. You’ll work with cross‑functional teams in prompt optimization, large language model (LLM) frameworks, and conversational AI evaluation protocols, ensuring AI products deliver measurable business value. :contentReference[oaicite:0]{index=0}

Key Responsibilities

• Establish and maintain Skit.ai’s AI Engineering CoE with best practices, documented frameworks, and prompt libraries. :contentReference[oaicite:1]{index=1}
• Develop standardized prompt templates and evaluation protocols for ASR/TTS and voice assistant use cases. :contentReference[oaicite:2]{index=2}
• Analyze conversational AI performance, identify trends and optimization opportunities, and trace performance issues back to design decisions. :contentReference[oaicite:3]{index=3}
• Generate insights reports highlighting improvements and business impact. :contentReference[oaicite:4]{index=4}
• Collaborate with engineering, data, and delivery teams to integrate insights into product development workflows. :contentReference[oaicite:5]{index=5}
• Support A/B testing of prompt variations and evaluate feature impacts on KPIs. :contentReference[oaicite:6]{index=6}
• Mentor AI engineers on best practices and emerging innovations in conversational AI. :contentReference[oaicite:7]{index=7}

Skills & Qualifications

• 3–6 years in product analysis, AI/ML product roles, or conversational AI development. :contentReference[oaicite:8]{index=8}
• Hands‑on experience with LLM prompting techniques and frameworks. :contentReference[oaicite:9]{index=9}
• Strong analytical skills with proficiency in Python or similar data tools. :contentReference[oaicite:10]{index=10}
• Experience designing and analyzing controlled experiments (such as A/B tests). :contentReference[oaicite:11]{index=11}
• Deep understanding of NLP, conversational AI, and voice bot architectures. :contentReference[oaicite:12]{index=12}
• Ability to translate large datasets into actionable product insights. :contentReference[oaicite:13]{index=13}

💰 Salary & Compensation

While the job posting does not list specific compensation, salary data for roles at Skit.ai suggests competitive packages that vary by experience and position level. Average software engineer compensation at Skit.ai in Bengaluru is around ₹26.3 L per year (median figure), and higher levels such as Product/Engineering leadership roles can exceed ₹40 L per year. :contentReference[oaicite:14]{index=14}

Compensation may include base salary, bonuses, and performance incentives depending on company policies and performance. :contentReference[oaicite:15]{index=15}

🏢 About Skit.ai

Skit.ai is a leader in **Conversational AI**, creating next‑generation voice and message AI assistants to transform customer engagement workflows. The company’s flagship Collection Orchestration Platform synchronizes communications across channels, optimizing interactions via its proprietary Large Collection Model (LCM) for improved efficiency and outcomes. :contentReference[oaicite:16]{index=16}

Founded in 2016, Skit.ai operates globally with headquarters in New York City and a major innovation hub in Bangalore, serving enterprises with scalable AI solutions that elevate automation and user experience. :contentReference[oaicite:17]{index=17}

🌟 Company Culture & Work Environment

Skit.ai embraces a high‑innovation, fast‑paced product culture with a strong focus on AI and cutting‑edge technologies. Teams collaborate across product, research, and engineering disciplines to deliver advanced conversational solutions that drive measurable business outcomes. :contentReference[oaicite:18]{index=18}

Being a startup with a global footprint, Skit.ai emphasizes ownership, agility, and continuous learning — making it a rewarding environment for professionals passionate about AI and product impact. :contentReference[oaicite:19]{index=19}

⭐ Pros & Cons for Job Seekers

✅ Pros:

• Work on state‑of‑the‑art Conversational AI products and LLM‑driven solutions. :contentReference[oaicite:20]{index=20}
• Opportunity to influence core prompt engineering practices and product strategy. :contentReference[oaicite:21]{index=21}
• Exposure to large‑scale voice and messaging AI systems. :contentReference[oaicite:22]{index=22}
• Collaborative and innovative startup culture with global impact. :contentReference[oaicite:23]{index=23}

❌ Cons:

• Salary variance across roles and levels can be broad. :contentReference[oaicite:24]{index=24}
• High technical expectations and responsibilities in a rapidly evolving field. :contentReference[oaicite:25]{index=25}
• Startup environments may require adaptability to changing priorities. :contentReference[oaicite:26]{index=26}

🧠 Preparation Tips for This Role

• Enhance your understanding of **LLM prompting** techniques and best practices. :contentReference[oaicite:27]{index=27}
• Practice data analysis and visualization with Python, SQL, or similar tools. :contentReference[oaicite:28]{index=28}
• Build experience in A/B testing frameworks and experiment design. :contentReference[oaicite:29]{index=29}
• Study NLP fundamentals and conversational AI principles. :contentReference[oaicite:30]{index=30}
• Familiarize yourself with voice AI, ASR/TTS technologies, and evaluation metrics. :contentReference[oaicite:31]{index=31}

📈 Industry Trends & Outlook

Conversational AI continues to grow as enterprises adopt voice and chat assistants for scalable customer engagement. Innovations in prompt engineering, compliance‑aware design, and analytics are key trends shaping the market — making product analysis roles in AI engineering increasingly important across sectors like finance, contact centers, and enterprise automation. :contentReference[oaicite:32]{index=32}