Project Leader .NET

About the Company:

MyOperator is a Business AI Operator, a category-leader that unifies WhatsApp, Calls, and AI-powered chat & voice bots into one intelligent business communication platform. Unlike fragmented communication tools, MyOperator combines automation, intelligence, and workflow integration to help businesses run WhatsApp campaigns, manage calls, deploy AI chatbots, and track performance all from a single, no-code platform. Trusted by 12,000+ brands including Amazon, Domino's, Apollo, and Razorpay, MyOperator enables faster responses, higher resolution rates, and scalable customer engagement without fragmented tools or increased headcount.

About the Role:

MyOperator is looking for a motivated and customer-focused Customer Support Executive to join our dynamic team. This internship offers hands-on experience in handling customer queries, managing support tickets, and gaining exposure to the workings of a fast-growing SaaS company.

Key Responsibilities:

• Respond to customer queries via calls, emails, and support tickets.
• Assist in resolving issues related to panel access, call reports, and login problems.
• Update ticket statuses and maintain accurate customer records using Zoho Desk.
• Collaborate with the support team to escalate complex issues to relevant departments.
• Assist in creating and maintaining FAQs and troubleshooting documentation.

Requirements:

• Good communication skills in English(spoken and written).
• Basic computer proficiency and willingness to learn support tools and CRM systems.
• Strong interest in SaaS, tech support, or customer-facing roles.
• Availability for a full-time (Monday to Saturday, rotational shifts).

What You’ll Gain:

• Practical exposure to customer success and support operations in a SaaS environment.
• Opportunity to work with experienced professionals and learn industry best practices

Job title: Chief Agentic Quality Architect

Type: Full-Time | Contract

Location: Remote

Role Overview

Equity Partners builds profitable growth by acquiring and operating enterprise software companies — refining a proprietary operating model across 40+ acquisitions and two decades of hands-on experience, now supercharged by our patented agentic AI platform. We're hiring a Chief Agentic Quality Architect to lead the transition from traditional scripted testing to an AI-augmented quality ecosystem. In this role, you'll audit and rebuild our quality engineering foundations, deploy agentic automation across critical business flows, and build the guardrails needed to keep AI-generated code production-ready.

Key Skills

• 10+ years in QA automation engineering, SDET, or test architecture roles
• Expert-level proficiency in Playwright, Cypress, or Selenium
• Hands-on experience using LLMs (Claude, GPT-4, etc.) and agentic frameworks to generate code or automate workflows
• Deep understanding of integrating quality gates into AWS-based CI/CD pipelines or similar environments
• Architectural mindset, with the ability to design "Behavioral Snapshots" to safeguard critical business logic during rapid transformation

Responsibilities

• Conduct a comprehensive audit of the existing test estate across unit, integration, API, UI, sanity, and regression layers, producing a Current State & Gap Coverage Report
• Architect and own a phased quality engineering roadmap across two-week, one-month, and three-month delivery horizons
• Deploy agentic test generation — transforming business requirements into executable Playwright/Cypress scripts, generating synthetic test data, and implementing self-healing automation
• Design regression strategies and quality gates specifically tuned to catch hallucinations and logic errors in AI-generated code
• Build, mentor, and upskill a specialist QA team fluent in AI-assisted testing and agentic automation frameworks

If you're ready to rewrite the rules of quality for an AI-native world, we want you leading the charge.

-Promote and sell insurance products to potential clients.

-Assess client's needs and offer tailored coverage solutions.

-Build and maintain relationships with new and existing customers.

-Achieve sales targets and performance goals.

Who Should Apply?

-Effective Communication and sales ability

-Had good convincing skills and problem solving skills.

-Should have a good acumen for Sales.

-Good in interacting with peoples.

-Interpersonal skills to meet the targets and build customer relationships.

-Age: 20 to 30 years.

Role of a Quantitative Trader

Role and Responsibilities:

*Candidate is expected to have a rigorous quantitative aptitude and go-get attitude.

*Candidate will be monitoring closely quantitative models in Derivatives markets and manage the Risk of its open Positions

Requirements:

Education (Candidate should satisfy one of the following)

 B.Sc./M.Sc. Mathematics or B.Sc./M.Sc. Statistics from a reputed college with good grades

 B.Tech with good grades and strong quantitative aptitude

 CFA/FRM Level 1 cleared

 Any other degree with Financial Derivatives as a subject and through knowledge of Options Greeks (Portfolio Level, Risk Management, Hedging)

Preferences:

Following skill sets are not required but candidate will get preference if he/she possesses any of the following:

 Working knowledge of python for historical data analysis or working on real-time analytics getting feed from a web API (Data structures, numpy, scikit-learn, tensor flow)

 MATLAB/R for Time series analysis

 Knowledge of AFL ( Amibroker Formula Language)

Benefits and Advantages for Candidate:

 Steep learning curve

 Extensive training on mathematics of derivatives market

 Dynamic work environment.

 Merit based growth

 Quarterly bonuses Based on Performance post training period (where bonus can surpass the base salary)

Pay Structure:

 Extensive training period(probation period) of 3 months(Stipend Paid during training period INR 20,000)

 Pay Structure post the training period:

Base Salary of 5 Lacs p.a  + Performance Bonuses

Working Hours:

We neither believe in staying unnecessary in office if there's nothing productive to be done nor do we believe in long unproductive lunch breaks.

 Standard Market Hours : 8:45 – 5.00 p.m

 Training Pre and Post market hours

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has  world class investors and big data experts as part of the GP,  top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

• Atleast 3 years of relevant ML experience
• Graduation date : 2018 and earlier
•   3-5 years of experience in high level Python programming.
• Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
•   Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques. 
•   Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
• Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
•   Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling. 
•   Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
•   A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
• A valid Github profile with some activity in it

Bonus to have:

•   Experience in storing and retrieving data from large and complex time series databases
•   Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
•   Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation. 
•   Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.) 
•   Knowledge of REST APIs and data extracting and cleaning techniques 
•   Good to have experience in Pyspark or any other big data programming/parallel computing
•   Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
•   Any progress towards CFA or FRM is a bonus
• Average tenure of atleast 1.5 years in a company