l2/l3 Protocols Testing & Automation

Location: Remote / Work From Home

Experience: 3–5 Years

What You'll Do

• Configure and manage Jira Service Management (JSM).
• Implement ITSM processes, including Incident, Change, Problem, and Request Management.
• Create and customize workflows, automation rules, and dashboards.
• Integrate Jira Service Management with Confluence and third-party tools.
• Provide technical support and continuously optimize service management processes.

Requirements

• 3–5 years of hands-on experience with Jira Service Management (JSM).
• Strong understanding of ITIL and ITSM best practices.
• Experience with Jira Administration, JQL, and Automation.
• Knowledge of Confluence and REST API integrations.
• Excellent communication and problem-solving skills.

Experience: 6+ years building and operating production ML systems that drive commercial decisions at scale. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pag05ROZwgz5AaLDG/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds decisioning infrastructure for enterprise customers: ranked recommendations, scoring pipelines, and policy-governed outputs that drive real commercial action. Our ML systems do not live in notebooks. They run multi-stage evaluation harnesses, apply structured governance rules, backtest against historical outcomes, and ship ranked outputs that customers act on daily.

This role owns the decisioning system end to end. That means the models, the eval harness, the policy layer, the production services, and the technical roadmap for where all of it goes next.

What You Will Do

Own the decisioning and ranking pipeline. Design, extend, and operate the end-to-end system: candidate generation in DuckDB, multi-stage scoring with LightGBM and AutoGluon, post-score policy application, and final ranked output delivery. You understand each layer well enough to debug latency, correctness, and coverage problems quickly, and to design the next version.

Lead the evaluation harness. Our eval pipeline runs multiple gates before any output ships: data health checks, specification validation, business rules enforcement, resolution checks, LLM-as-judge scoring, backtest against historical outcomes, and final output validation. You will own this harness, extend it as the system grows, and ensure every model or pipeline change is measurable and reproducible before it reaches a customer.

Apply policy logic with rigor. Our ML systems operate under structured governance rules that determine which offers apply to which customer segments, under what conditions. You will implement, test, and audit these rules in code, not configure them in a spreadsheet. Every exclusion must be traceable and explainable.

Engineer features that move metrics. Identify and build the behavioral signals, engagement indicators, contract features, and value-band attributes that improve model performance. Close the loop from feature hypothesis through offline evaluation to production monitoring. Own the data contracts between upstream sources and the scoring pipeline.

Build and maintain the production pipeline and service layer. The decisioning system is not a batch notebook. You will write and operate the Python pipeline and service layer that wraps model inference, handles edge cases, versions model artifacts, and connects to downstream consumers. You own CI, test coverage, reproducible training runs, monitoring, and production incidents.

Drive technical direction. Write design documents, lead code review, and set the engineering standard for the decisioning system. Help define the roadmap: what gets built, in what order, and why. Mentor contributors who work alongside you on this system.

Work forward-deployed. You will engage directly with customer stakeholders to understand business context, interpret model outputs, and translate commercial requirements into system constraints. You are accountable for customer delivery, not just model accuracy.

What We Are Looking For

• 6+ years building and operating production ML systems, not prototypes or research work
• Strong Python skills across the full ML lifecycle: data pipelines, feature engineering, model training, inference services, and monitoring
• Production experience with gradient boosting models (LightGBM, XGBoost)
• Hands-on with DuckDB or similar in-process analytical engines for large-scale data processing
• Evaluation discipline: held-out metrics, backtesting against historical data, multi-gate eval pipelines, LLM-as-judge patterns
• Experience applying business rules, policy overrides, or constraint layers on top of model outputs
• Engineering fundamentals: CI pipelines, data contracts, versioned artifacts, test coverage, incident response
• Technical leadership: design docs, code review, roadmap input, mentoring
• Comfort with forward-deployed work: you can run a meeting with a non-technical stakeholder and turn the output into a system requirement
• Comfort inheriting an existing production codebase, improving its structure, and raising reliability without rewriting everything from scratch

Bonus Points

• Experience with next-best-offer engines, customer-level targeting, or recommendation systems at scale
• Experience with AutoML frameworks (AutoGluon or similar) in a production scoring pipeline
• Thompson sampling, multi-armed bandits, or portfolio-level optimization experience
• Exposure to structured data from telecoms, financial services, or retail sectors
• Prior work owning a decisioning or ranking system as the technical lead

Life at Terrabase

We are a sharp, focused, fully remote team that ships to real enterprise customers weekly. You will own a system that drives measurable commercial outcomes, with high autonomy, generous cloud budgets, and a culture that prizes rigor over hype.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

Job Title: Talent Acquisition Associate

Location: Worli, Mumbai (Hybrid Working)

Experience: 1-2 years

About Qrata

We match top talent with highly competitive career opportunities with leading startups in India

and globally and address hiring challenges, recruitment brand marketing, with innovative and

collaborative strategic consulting.

Position Overview:

As a Talent Acquisition Associate at Qrata, you will be an essential part of our human resources team, responsible for sourcing, attracting, and hiring talented professionals. You will work closely with hiring managers to understand their staffing needs and ensure we bring in the best talent to support our company's growth. This position offers the opportunity for hybrid working, combining both remote and in-office collaboration, with our office located in Worli, Mumbai.

Key Responsibilities:

• Collaborate with hiring managers to understand job requirements and create detailed job descriptions.
• Develop and implement effective talent acquisition strategies to attract high-quality candidates.
• Source candidates through various channels, including job boards, social media, and professional networks.
• Screen and evaluate resumes and applications to identify potential candidates.
• Conduct initial interviews to assess candidate qualifications and cultural fit.
• Coordinate and schedule interviews with hiring managers.
• Manage the recruitment process from start to finish, ensuring a smooth and positive candidate experience.
• Extend job offers and negotiate terms with candidates.
• Build and maintain a talent pipeline for future staffing needs.
• Assist with other HR-related tasks and projects as needed.

Qualifications:

• 1-2 years of experience in talent acquisition or recruitment.
• Knowledge of recruitment best practices and sourcing techniques.
• Strong communication and interpersonal skills.
• Proficiency with applicant tracking systems and HR software.
• Ability to work both independently and collaboratively in a team.
• Excellent organizational and time management skills.
• Familiarity with employment laws and regulations.

Key Skill :

- JavaScript with Dom Manipulation

- Good understanding on AJAX concepts

- Know jQuery implementation with its libraries

- Front-End Framework - Bootstrap knowledge

- In-Depth knowledge of PHP and its framework CodeIgniter

- In-Depth knowledge of Relational Database - MySQL

- Integration of Third Party Code Snippets.

- Knowledge of deployment the project on the production server

- Restful API Design and Development with CRUD Functionality

- Git/Github Knowledge

- Must be open to learn new technologies and frameworks as per the project's requirements

- Must have ability to work under pressure while performing priority tasks

- Must have critical and analytical skills

- Must be a quick and self-learner

Add on Benefits :

- Knowledge of Jira, Git and Digital Ocean are the key benefits.

• 12+ years of experience in software development with least 3 years of experience as an Enterprise Architect
• Proven and demonstrable experience in creating scalable solutions
• Proven experience with leading large-scale builds, with multiple squads running at the same time
• Familiar with production Cloud / DevOps environments
• Strong analytical and problem-solving skills paired with the ability to develop creative and efficient solutions
• Good leadership and motivational skills
• Excellent interpersonal, oral, and written communication skills
• Experience in modeling and graphic representation

Technology / Tools :-

• Digital Lending Stack
• SFDC
• AWS services

Good to have skills:-

• Open-source contribution
• SFDC certification
• TOGAF 9 Certification

Key responsibilities

• Evaluate internal functions, business development strategies, and IT processes; suggest improvements
• Create business architecture models to reflect the organization's strategies and goals; create and implement business visions and goals by solutioning new implementations/improvements
• Facilitate decision making on technology architecture, build versus buy strategies and vendor (keeping in mind the IT cost)
• Architectural leadership in the resolutions of inter-program and inter-project issues; problem solve on tech challenges faced
• Audit compliance with the Enterprise Architecture standards
• Ongoing publicity and communication of the Enterprise Architecture both within the IT community, and the business units
• Ongoing research and assessment of new analysis approaches for potential use within the Enterprise
• Mentor and Coach the technical team to effectively build solutions; organize training to improve employees' knowledge and skills for future organizational growth
• Thought partner with the CIO on people, process, and platform decision