Lead Software Engineer [Multiple Positions Available]

We need to output HTML fragment with sections: About the role? Actually description includes duties, qualifications, skills, location, full-time, about us, about the team. We need to use headings for sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We only include sections that have real specific content. We have duties (Responsibilities). We have qualifications (Minimum education and experience required). We have skills required (Skills). We have location and full-time maybe could be part of About the role? But we can include a short paragraph for location and schedule? The posting says Full-Time. That's schedule info. So we can include a Schedule section with "Full-Time". Pay: not specified (they mention competitive total rewards package, base salary determined based on role, experience, skill set and location, commission-based pay etc). That's vague but they say "competitive total rewards package including base salary determined based on the role, experience, skill set and location." That's not a specific number; but it's still some info about pay. The rule: never emit a heading followed by filler/placeholder text (e.g. "commensurate with experience", "not specified", "N/A", "varies", "TBD") and never create Pay/Schedule/Benefits sections unless the posting actually states them. For Pay, they do state some info: base salary determined based on role, experience, skill set and location; also mention commission-based pay and/or discretionary incentive compensation. That's not a specific number but it's still substantive? It's somewhat generic but still states that pay is based on role etc. Might be acceptable. However they also mention benefits: they list benefits in About Us: comprehensive health care coverage, on-site health and wellness centers, retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. That's specific benefits. So we can include Benefits section. Schedule: they say Full-Time. That's specific. So we can include Schedule section with "Full-Time". Pay: they mention base salary determined based on role, experience, skill set and location; also commission-based pay and/or discretionary incentive compensation. That's not a specific number but it's still info. I'd include Pay section with that description. We must not repeat job title as heading. We'll not include Job ID. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to preserve all substantive information. So we need to include duties list, qualifications, skills list, location, full-time, about us (maybe as About the role? Actually About Us is separate but we could incorporate into About the role? The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can put About the role as a short paragraph summarizing the role (maybe from description). But we have duties already; we could put About the role as a brief overview: "Develop and maintain data storage and processing solutions..." Actually that's duties. Might duplicate. Better to treat About the role as a short paragraph describing the role (maybe from first sentence). But we must not invent or summarize away detail. We can reuse the first sentence: "Develop and maintain data storage and processing solutions to support efficient data management and analytics, utilizing modern cloud and on-premises technologies such as data lakes and distributed databases." That's part of duties. If we put it in About the role, we still need to include duties elsewhere? Could combine. But we need to preserve all substantive information; we can put duties under Responsibilities heading as a list. About the role could be a short paragraph summarizing the role (maybe from the first paragraph). However we risk duplication but it's okay as long as we preserve info. The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." Duplication is not prohibited. So we can include both. We need to remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The About Us includes EEO statements; we need to remove those. Also remove the "About The Team" maybe? It's not a required heading but could be part of About the role? It's substantive about team; we could include it under About the role or maybe as a separate section? Not in allowed headings list. Probably we should incorporate relevant info into About the role or maybe drop it? The instruction: "include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text". The allowed headings are given but we can also have other headings? It says use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It implies we should use those headings for sections. Likely we should only use those headings. So we need to map content to those headings. Thus: - About the role: maybe a brief overview from the description: "Develop and maintain data storage and processing solutions to support efficient data management and analytics, utilizing modern cloud and on-premises technologies such as data lakes and distributed databases." plus maybe mention team? Could incorporate About The Team info: "J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments." That's about the team. Could be part of About the role. - Responsibilities: list of duties (the bullet points after Duties:). We'll convert each sentence into

  . - Requirements: maybe the qualifications? Actually they have Qualifications heading. Requirements could be something else like "Minimum education and experience required". But we have Qualifications heading separate. The instruction list includes Requirements and Qualifications both. We need to decide what goes where. Usually Requirements could be the minimum education and experience; Qualifications could be skills? But they also have Skills heading. Let's map: - Requirements: maybe the minimum education and experience required (Bachelor's degree plus 7 years experience). Could be considered requirements. - Qualifications: maybe the "Skills Required" list? But they also have Skills heading. Hmm. Better to follow typical job posting: Requirements = education/experience; Qualifications = maybe additional qualifications? But they also have Skills. The posting has "Qualifications Minimum education and experience required:" then "Skills Required:" So we can treat: - Requirements: the education/experience. - Qualifications: maybe the "Skills Required"? But they also have Skills heading. Could treat Qualifications as the skills list and Skills as maybe something else? But they'd be duplicate. Given the instruction list includes both Requirements and Qualifications and Skills, we should try to use all three if content fits. We have: - Education/experience: Bachelor's degree in ... plus 7 years experience. - Skills Required: a long list of specific skills (Python, ML, AWS, etc.) Thus we can assign: - Requirements: education/experience. - Qualifications: maybe the "Skills Required"? But then Skills heading would be duplicate. Could we put Skills as maybe the "Skills Required" and Qualifications as something else like "Designing, implementing, and optimizing machine learning algorithms..."? That's part of skills. Better: Use Requirements for education/experience, Qualifications for the skills list (since they are qualifications), and Skills maybe we could omit if no distinct content. But we need to include a section only when posting has real specific content for it. If we put Skills heading but no distinct content beyond what's in Qualifications, that would be filler. So we should omit Skills heading if we already used Qualifications for skills. Thus we will have sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay, Schedule. We need to include Benefits from About Us: list of benefits. Pay: base salary determined based on role, experience, skill set and location; commission-based pay and/or discretionary incentive compensation. Schedule: Full-Time. Now we need to format. We'll produce:

  About the role

  Develop and maintain data storage and processing solutions to support efficient data management and analytics, utilizing modern cloud and on-premises technologies such as data lakes and distributed databases. J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments, providing strategic advice, raising capital, managing risk and extending liquidity in markets worldwide.

  Responsibilities

  • Develop and maintain data storage and processing solutions to support efficient data management and analytics, utilizing modern cloud and on-premises technologies such as data lakes and distributed databases.
  • Build and optimize applications for data ingestion, transformation, and retrieval, leveraging scalable storage and database platforms.
  • Create automated extract, transform, and load (ETL) processes and optimize data pipelines for reliability and performance using orchestration and data engineering tools.
  • Support complex data analytics and reporting needs by integrating with enterprise data platforms and business intelligence tools.
  • Implement real-time and batch data processing solutions for analytics and machine learning using distributed computing frameworks including Apache, Spark, and Flink.
  • Design, train, and deploy machine learning (ML) and AI models to address business challenges, including predictive analytics and decision support.
  • Develop and maintain models and systems for fraud detection and risk mitigation, ensuring alignment with industry best practices and regulatory requirements.
  • Use infrastructure automation tools to provision, manage, and scale cloud and on-premises resources efficiently.
  • Build and deploy serverless solutions to enable flexible, scalable, and cost-effective application architectures.
  • Implement strategies to monitor, manage, and reduce cloud infrastructure expenses while maintaining performance and reliability.
  • Maintain compliance with relevant regulations and standards, and implement robust data security and governance practices.

  Requirements

  Bachelor's degree in Electrical Engineering, Electronic Engineering, Computer Engineering, Computer Information Systems, or related field of study plus 7 years of experience in the job offered or as Lead Software Engineer, Software Engineer/Developer, Programmer Analyst, Technical Lead, or related occupation.

  Qualifications

  • Experience designing, implementing, and optimizing machine learning algorithms and AI solutions using Python; data preprocessing, feature engineering, model selection, and hyperparameter tuning.
  • Developing end-to-end ML pipelines, from data ingestion to model deployment and monitoring, to ensure scalability and robustness.
  • Architecting and deploying scalable data processing workflows using AWS Glue for ETL, AWS Athena, Step Functions for orchestration, S3, and elastic map reduce for distributed data analytics.
  • Designing cloud-native solutions leveraging AWS services with security, cost optimization, and high availability.
  • Utilizing cloud data warehousing features to enable complex queries, data modeling, and business intelligence.
  • Applying best practices for data validation, cleansing, and governance within cloud data environments.
  • Developing and maintaining data models, data lakes, and data warehouses.
  • Implementing analytics solutions and optimizing query performance and data flow.
  • Authoring and maintaining Terraform scripts to automate cloud infrastructure provisioning and management, repeatability, and compliance.
  • Developing and deploying serverless applications and integrating them with AWS Lambda for event-driven processing.
  • Building and enhancing fraud detection models, including feature engineering, entity resolution, and real-time scoring by using domain-specific techniques.
  • Identifying fraud patterns and translating business requirements into effective ML solutions.
  • Developing, validating, and deploying supervised, unsupervised, and reinforcement learning models.
  • Evaluating model performance using metrics and implementing strategies for continuous improvement.
  • Applying deep learning techniques using TensorFlow, PyTorch, Keras, or Scikit-learn for model development, training, and evaluation.

  Benefits

  • Comprehensive health care coverage
  • On-site health