CICS System Programmer

Key Responsibilities:

• Proactively reach out to potential leads and convert them into active clients.
• Explain the account opening process clearly and assist clients in completing documentation and KYC requirements.
• Guide clients through broker platform registration (e.g., MT4/MT5).
• Follow up regularly to ensure clients fund their trading accounts.
• Coordinate with broker partners to resolve onboarding issues or delays.
• Maintain accurate records of client progress in CRM and report daily/weekly updates to the team lead or manager.
• Educate clients on basic platform use, signal access, and trading readiness.
• Act as the first point of contact for new clients and ensure a positive onboarding experience.

Qualifications:

• Minimum Graduate or Post Graduate.
• Excellent communication and interpersonal skills.
• Basic understanding of trading platforms (MT4, MT5, etc.) and brokerage operations is a plus.
• Goal-oriented, organized, and self-motivate.

Job Description

Phonologies is seeking a Senior Data Engineer to lead data engineering efforts for developing and deploying generative AI and large language models (LLMs). The ideal candidate will excel in building data pipelines, fine-tuning models, and optimizing infrastructure to support scalable AI systems for enterprise applications.

Role & Responsibilities

• Data Pipeline Management: Design and manage pipelines for AI model training, ensuring efficient data ingestion, storage, and transformation for real-time deployment.
• LLM Fine-Tuning & Model Lifecycle: Fine-tune LLMs on domain-specific data, and oversee the model lifecycle using tools like MLFlow and Weights & Biases.
• Scalable Infrastructure: Optimize infrastructure for large-scale data processing and real-time LLM performance, leveraging containerization and orchestration in hybrid/cloud environments.
• Data Management: Ensure data quality, security, and compliance, with workflows for handling sensitive and proprietary datasets.
• Continuous Improvement & MLOps: Apply MLOps/LLMOps practices for automation, versioning, and lifecycle management, while refining tools and processes for scalability and performance.
• Collaboration: Work with data scientists, engineers, and product teams to integrate AI solutions and communicate technical capabilities to business stakeholders.

Preferred Candidate Profile

• Experience: 5+ years in data engineering, focusing on AI/ML infrastructure, LLM fine-tuning, and deployment.
• Technical Skills: Advanced proficiency in Python, SQL, and distributed data tools.
• Model Management: Hands-on experience with MLFlow, Weights & Biases, and model lifecycle management.
• AI & NLP Expertise: Familiarity with LLMs (e.g., GPT, BERT) and NLP frameworks like Hugging Face Transformers.
• Cloud & Infrastructure: Strong skills with AWS, Azure, Google Cloud, Docker, and Kubernetes.
• MLOps/LLMOps: Expertise in versioning, CI/CD, and automating AI workflows.
• Collaboration & Communication: Proven ability to work with cross-functional teams and explain technical concepts to non-technical stakeholders.
• Education: Degree in Computer Science, Data Engineering, or related field.

Perks and Benefits

• Competitive Compensation: INR 20L to 30L per year.
• Innovative Work Environment for Personal Growth: Work with cutting-edge AI and data engineering tools in a collaborative setting, for continuous learning in data engineering and AI.

• Highly customer-obsessed thinking with a deep understanding of customerneeds and aspirations
• Own the product strategy and roadmap.- Partner with the business team tounderstand business goals and translate them into short term and long-term productroadmaps.- Comfortable in generating a 3-year strategic vision as well as a weekly statusupdate.
• Generate detailed Product Requirement Document (PRD) based oninputs from all key stakeholders.Integrate usability studies, research and market analysis intoproduct requirements to maximise user satisfaction.
• Work very closely with world-class Engineering, Data Sciences and QA teams throughout the product development life cycle.- Define the product acceptance testingcriteria, ensure that they are met.
• Stay abreast with new innovations and the latest technology trends andexplore ways of leveraging these for improving the product in alignment with the business.
• Attention to detail with an ability to work with user interfacedesigners and usability experts to deliver habit-forming products with a low learning curve