Senior AI Application Engineer

This role is for one of the Weekday's clients

Salary range: Rs 2500000 - Rs 3500000 (ie INR 25 - 35 LPA)

Min Experience: 5 years

Location: Bengaluru

JobType: full-time

This role requires a strong blend of technical expertise and customer-focused problem-solving. You will configure, troubleshoot, and optimize AI solutions for our customers, ensuring high performance, continuous improvement of customer workflows, and exceptional customer satisfaction. You will independently manage complex deployments and solutions for enterprise customers with minimal guidance.

Requirements:
Your Responsibilities:

Key Roles and Responsibilities

Set up and connect AI/GenAI workflows by utilizing platform APIs and customer data, ensuring a seamless and secure deployment process.

Convert customer requirements into technical solutions, verifying the accuracy of workflows and continuously optimizing prompts for enhanced performance.

Create and automate tasks leveraging Python & SQL, while developing prototypes using open-source Agentic Frameworks to enhance customer experience workflows.

Design, execute, and evaluate A/A experiments to assess and improve the quality and reliability of workflows.

Oversee AI workflows through business metrics and observability dashboards, promptly addressing any issues to maintain high availability.

Offer proactive solutions and consistent updates to customers, ensuring high customer satisfaction through effective troubleshooting and clear communication.

Identify and rectify platform issues concerning APIs, data integration, and workflow configurations, collaborating with the engineering team when necessary.

Employ APIs and integration protocols (JSON, REST, SOAP) to set up workflows and integrate with CRM/ATS systems.

Create custom scripts to query databases and generate reports for comprehensive analysis and to showcase ROI to customers.

Preferred Qualifications:

Experience:

4+ years of experience in software engineering.

Extensive experience in the development of AI/LLM applications, including the creation of agents, integrations, workflows, and assessing/improving their performance.

Background in establishing, configuring, and maintaining ML Systems or AI Agents is advantageous.

Experience in developing LLM-based evaluation frameworks and conducting user acceptance tests with real customers.

Expertise in prompt engineering techniques.

Proven ability to independently manage complex deployments and solution designs for enterprise customers with minimal oversight.

Understanding of essential support metrics (FRT, AHT, TAT, CSAT) and reporting methodologies.

Strong troubleshooting and problem-solving capabilities, particularly in production settings. Ideal candidates should be adept at diagnosing ML performance challenges and recommending solutions to enhance accuracy metrics and other business KPIs.

Exceptional communication skills to effectively collaborate with both technical and non-technical stakeholders.

Technical Proficiencies:

Expertise in Python & SQL scripting.

Knowledge of Data Structures & Algorithms is advantageous.

Experience with prompt engineering techniques.

Proficient in leveraging platform APIs to retrieve or send data and configure workflows.

Familiarity with JSON, REST, SOAP, or other integration protocols, as well as integrating prominent CRM/ATS tools is a plus.

Data-driven assessment skills, including the ability to set up and interpret A/A experiments.

Experience with logging, dashboard creation, and alerting tools.

Interpersonal Skills:

Strong communication skills to effectively collaborate with both technical and non-technical stakeholders.

Demonstrated ability to manage intricate deployments and solution designs for enterprise customers autonomously.

Robust troubleshooting and problem-solving skills, particularly in production environments.

Ownership & Initiative: Demonstrates accountability for ongoing workflow management and customer outcomes.

Curiosity & Continuous Learning: Proactively investigates new GenAI/automation methodologies and best practices to enhance workflows.

Collaboration: Works efficiently with multiple teams.

Customer Empathy: Focuses on customer success criteria, ensuring that solutions meet real business needs.