AI Developer (Quant Developer)

Luxoft; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

A leading IT services company in Bengaluru seeks a Senior Recruiter to lead the design and implementation of advanced AI and ML models for market abuse detection. The role demands 7+ years of experience and expertise in collaboration with cross-functional teams to ensure regulatory compliance. Candidates should be adept in Python, PySpark, SQL, and storytelling to bridge technical gaps. Excellent mentorship and problem-solving skills are essential for integrating complex solutions in a fast-paced financial environment.

Responsibilities

• Architect and implement scalable AI/ML models for detecting market abuse patterns.
• Collaborate to gather requirements and co-create innovative solutions.
• Translate regulatory and business requirements into actionable technical designs.
• Develop solutions to aggregate and analyze trading data.
• Design and optimize real-time and batch processing pipelines.
• Build statistical and machine learning models for anomaly detection.
• Ensure solutions comply with global Market Abuse Regulations.
• Lead code reviews and mentor junior developers.
• Integrate surveillance models with existing compliance platforms.
• Conduct back‑testing and performance benchmarking.

Skills

Advanced AI/ML modelling (Python, PySpark, MS Copilot, kdb+/q, C++, Java)

Statistical analysis and anomaly detection

Large-scale data engineering and ETL pipeline development

SQL (preferably Spark SQL)

Regulatory compliance (MAR, MAD, MiFID II, Dodd‑Frank)

Strong storytelling and communication

Leadership and mentoring

Problem-solving and critical thinking

Adaptability and continuous learning

Job description

Senior Recruiter at Luxoft, A DXC Technology Company

Project Description:

• Lead the design and development of advanced quantitative and AI‑driven models for market abuse detection across multiple asset classes and trading venues. Drive the solutioning and delivery of large‑scale surveillance systems in a global investment banking environment, leveraging Python, PySpark, big data technologies, and MS Copilot for model development, automation, and code quality. Play a pivotal role in communicating complex technical concepts through compelling storytelling, ensuring alignment, and understanding across business, compliance, and technology teams.

Responsibilities

• Architect and implement scalable AI/ML models (using MS Copilot, Python, PySpark, and other tools) for detecting market abuse patterns (e.g., spoofing, layering, insider trading) across equities, fixed income, FX, and derivatives.
• Collaborate closely with consultants, MAR monitoring teams, and technology stakeholders to gather requirements, share insights, and co‑create innovative solutions.
• Translate regulatory and business requirements into actionable technical designs, using storytelling to bridge gaps between technical and non‑technical audiences.
• Develop cross‑venue monitoring solutions to aggregate, normalize, and analyze trading data from multiple exchanges and platforms using big data frameworks.
• Design and optimise real‑time and batch processing pipelines for large‑scale market data ingestion and analysis.
• Build statistical and machine learning models for anomaly detection, behavioural analytics, and alert generation.
• Ensure solutions are compliant with global Market Abuse Regulations (MAR, MAD, MiFID II, Dodd‑Frank, etc.).
• Lead code reviews, mentor junior quant/developers, and establish best practices for model validation and software engineering, with a focus on AI‑assisted development.
• Integrate surveillance models with existing compliance platforms and workflow tools.
• Conduct back‑testing, scenario analysis, and performance benchmarking of surveillance models.
• Document model logic, assumptions, and validation results for regulatory audits and internal governance.

Mandatory Skills

• 7+ years of experience
• Advanced AI/ML modelling (Python, PySpark, MS Copilot, kdb+/q, C++, Java)
• Proficient in SQL with 2–4 years of production‑grade experience (preferably Spark SQL)
• Familiarity with Cross‑Product and Cross‑Venue Surveillance Techniques and vendors such as TradingHub, Steeleye, Nasdaq or NICE
• Statistical analysis and anomaly detection
• Large‑scale data engineering and ETL pipeline development (Spark, Hadoop, or similar)
• Market microstructure and trading strategy expertise
• Experience with enterprise‑grade surveillance systems in banking
• Integration of cross‑product and cross‑venue data sources
• Regulatory compliance (MAR, MAD, MiFID II, Dodd‑Frank)
• Code quality, version control, and best practices
• Strong storytelling and communication for technical and non‑technical audiences
• Collaboration with consultants, MAR monitoring teams, and technology stakeholders
• Stakeholder management and requirements gathering
• Leadership, mentoring, and team guidance
• Problem‑solving and critical thinking
• Adaptability and continuous learning

Nice‑to‑Have Skills

• Understanding of Financial Markets Asset Classes (FX, FI, Equities, Rates, Commodities & Credit), various trade types (OTC, exchange traded, Spot, Forward, Swap, Options) and related systems is a plus
• Surveillance domain knowledge, regulations (MAR, MIFID, CAT, Dodd Frank) and related Systems knowledge is certainly a plus

Seniority Level

Mid-Senior level

Employment Type

Full‑time

Job Function

Information Technology, Engineering, and Project Management

Industries

IT Services and IT Consulting and Software Development